MANUFACTURING SYSTEM MAINTENANCE DEVELOPMENT

by

Brennan P. Bowen

Report submitted to the Faculty of the

Virginia Polytechnic Institute and State University

in partial fulfillment of the requirements for the degree of

MASTER OF ENGINEERING

IN

INDUSTRIAL AND SYSTEMS ENGINEERING

APPROVED:

oe Gary

Prof. B.S. Blanchard, Chairman

Ve hed Me W. Fey Dr. K. P. Glllis Dr. W.J. Fabrycky

December 1996

' Blacksburg, Virginia

Keywords: Maintenance, Failure, Reliability, FMEA, RCM

Lp 5655 N86 1

1996 B6a4

MANUFACTURING SYSTEM MAINTENANCE DEVELOPMENT

by

Brennan P. Bowen

Prof. B.S. Blanchard, Chairman

Industrial and Systems Engineering

(ABSTRACT)

In this report, the Process Failure Modes and Effects Analysis (PFMEA)

and the Reliability-Centered Maintenance (RCM) analysis are used in tandem to

initialize a cost-effective maintenance plan for the Amada HFA-330 band saw.

The intent of this report is to describe and demonstrate how the two analyses

are used to develop the maintenance plan.

As part of the maintenance plan development, consideration is given to

the effects of processor down time on the throughput and profitability of the

manufacturing system. Any processor failure that decreases throughput of the

manufacturing system will create a loss in opportunity to fulfill demand.

After determining a maintenance plan, data should be collected from the

system to reaffirm or revise the maintenance decision. Data collected from the

manufacturing system may provide move accurate estimates allowing the

analyst to reiterate the procedures and improve the plan.

This methodology would be useful in the design phase to assess the life-

cycle cost of a system design. This methodology can be used to estimate the

cost of maintenance. The life-cycle cost of the system can then be estimated

from estimates of research and development, construction, start-up, operation

and maintenance, and system disposal estimates. Given multiple alternatives, a

decision on the preferred system can be made based on life-cycle costs.

Acknowledgments

The opportunities given me as an associate with the Systems Engineering

Design Laboratory (SEDL) were the source of my motivation for this project. |

took great interest in SEDL’s project with Federal Mogul Corporation in applying

the Process Failure Modes and Effects Analysis as a too! for process

improvement. While assisting the SEDL with this project, | learned of other

applications for this tool. Thank you Dr. Fabrycky and Professor Blanchard for

those opportunities. Thank you Dr. Verma for patience and guidance through

our work together. Thank you Dr. Ellis for your attention to detail and willingness

to serve on my graduate committee. Thank you Lovedia Cole for keeping the

formalities in order. | have enjoyed researching this topic.

Table of Contents

1.0 INtrOGUCTION .......:ccscccsscnsersnsnnserssnsaesonnnsessunaseeeusunseerauacsersaneasesosouauesonsegeeseneass 1

1.1 Identification of Opportunity ................. ccc cccccccsesseseeeeseeeeseeeeseesaeeseesesseeaeeeeeees 1 1.2 The Objective of the Project..................cccccccccseeesesseeeeeeeeeeeeeaaeaaeeeceeeeteeeesennenes 2

2.0 Manufacturing Systems Backgroui.........:ccsssssseeseccsscessseerecsennavereeeancenees 7

2.1 The Nature of Failure................c.cccccccccceseeecceceeeseesceecesnenesceeeesessacaeceesensaeaeees 10 2.2 Failure Assessment Through Effectiveness Measures...................::::ccee 14

2.3 Failure Assessment Through Cost Measures. .................cccccsseeeeseeeeeeneeeeeees 16 2.4 Defining the Manufacturing System.............0... cc eecceceececseeseeeeeeseeeeesseeeeees 18

3.0 Process Failure Modes and Effects Analysis (PFMEA) .............ssssssse 21

3.1 INTFOCUCTION 0.00... eecccceeeccesseceenerenscceceaseseeueeseescceeaeseceueeessaeeesensessausessaeeene 21

3.2 PFMEA Methodology ..................ccccceececceceeeeecereeeeeeeeeeeeenereeeeeeseeersteeteeeeeseeess 26 3.3 PFMEA Exa@mple.................ccccccccccccesesecceceesessececeeseenaeeceesesaaeasceeesseeaeseeeeseenees 29 3.4 Defining System Requirement ................::c:cccccceeececceeeeaeeaseseeeeeeeceeeeeneenaeees 31 3.5 Defining the Process FIOW..............ccccccccsesecccesssccneeeesecsensecessaeeecsaaaeseseeegsees 31 3.6 Functional Allocation ................cccccccsecccceseeceseecesesececesessenscsseeceseecenseeesseeess 33

3.7 Defining Failure Modes...................ccccccccccccceseseececaaseeeceeesecscsaaeseessaueeseeaaeeees 33 3.8 Defining Failure Causes ..............ccccccccccsesceseceeceeeseceseeceeeeeeeesesauegeceeeeseaaeness 37 3.9 Defining Failure Eff@cts 2.0.0.0... ccccecceccesssceeceeseceeseneeeeseensseeseeassessenanees 37

3.10 Identifying Current Controls .......... cc cccecceccccecceceeeeeceseeesseeeeseeseeeesssssaneneees 38 3.11 Defining Occurrence, Severity, and Detection. ............cccccceceeeeeseeeees 39 3.12 Determining Cost of Failure ........ 0... ccc cccccecceseeeseeesesereesessseeeneeseeessanaeees 39

4.0 Reliability Centered Maintenance Analysis ..............:ccccsscsssscsssserssreecesees 45

4.1 IMTPOGUCTION 0.00... c ccc cccnseeceeceeeesececeesesaneeeeseesauensceeeessaaaueeceeesseagaeeeeesnaes 45 4.2 Maintenance Significant ItEMS ..................cccccccccceeceeeeseeeereeseeeeteeeeeseaaenseeeeees 49 4.3 Structurally Significant IteMs 0.0.0.0... cceeceeccesceeeeeeeeeeseeeeseeeesseaaeeeeeeeeases 51 4.4 ROM DeCISION LOGIC 0.0.0.0... cee cccecceeseccceeeeseseeeeeccenensseeceeeeseaseneeeeeuenadseeeenaeaes 52 4.5 RCM Il Analysis Example ...................ccccccscecccessecseesesseseseeneeceeseseceeseeeeneeseees 54

4.6 Manufacturer's Recommended Maintenance Tasks.................cc:::csssseceeeees 57 4.7 Total-loss Lubrication Points .................ccccceeeeccesesceeseseneaeeeceseetesetseesersaes 59

4.8 Maintenance Task Decision LOGIC... cecccccsceesecseeneceeseeeeeessueeaceetan 59 4.9 ON-CONITION TASKS...............c.cccceeccccssesseeeseeeeessssesesseceenaeeesessegaeesesesssanaeeses 64 4.10 Scheduled Restoration Task................0cccccccccesescceceeeecceseeeeceeseneseeseaeseesees 65

4.11 Scheduled Discard Task................cccccccccccenseeseceeceseessececceseueaseesessesseseeesess 66 4.12 No Scheduled Maintenance (Corrective Maintenance) ......................00 67 4.13 Compulsory REdeSIGN .............cccccccccccecceseeeeseeeeeeeceseeseeeesseceeceeseaneneaeeaeaaaaes 68 4.14 Selecting the Maintenance Task..................cccccccccceceeseeneeeecsseeeeeeeesenensaaeees 68 4.15 Wallk-throughs ...0....... cc ccccceseeceeeeseeceessansaeesaeeeeeeseceseessaassensaseseeeeseeeneas 70

5.0 Maintenance Plan SUMMALPY.......:ccssssescsssssssessssesesvessessenecessenssssasorseasscenes 77

6.0 Conclusions and Recommendations ............ccssssessseseeeeeseesesonsenenseerersesens 77

Appendix A - RCM Decision Logic Diagrams. ...........:..:s:sessssssssssssessensensnenses 80

Appendix B - Maintenance Task AnalySis ................cessssenresssesssesncsssenseneensees 86

Appendix C - References and Additional Reading ............:::ssssesssssersesensers 90

Figure 1. Figure 2.

Figure 3. Figure 4. Figure 5.

Figure 6. Figure 7.

Figure 8.

Figure 9. Figure 10. Figure 10. Figure 10. Figure 11.

Figure 12. Figure 13.

Figure 15.

Figure 16. Figure 17. Figure 18. Figure 19. Figure 20. Figure 21.

Figure 22. Figure 23.

List of Figures

The PFMEA-RCM Relationship with a Feedback Loop...................... 5 Manufacturing System Throughput. ...................ccceceeeesseeeeeeeeeeeeeeeneees 9 Component P-F Interval. ............0... cc cecccccceesccceesseeeeceeseeeseaeseeessaaees 11

Reliability Profiles. ..............ccccccccssssesssseecceeeececeeaeueesseseeeeseeeeseeseeaanees 12 Manufacturing System Process FIOW. ...............:cccccccesseseeeeteeteeteeeeees 18 Sources of Information for the PFMEA. ..................:.ccccsssssseeeeeeeeeeeees 23 Identifying Production Constraints. ..................cccccccsssssceessseesenereneeeees 25

Identification of Machine Parts for Amada HFA-330. ....................0 30 Part Drawing: Incline Press Movement Arm. ..............::::ccseseeeeeeeenees 32 Band Saw Process Flow Diagram (Part 1). ..............cccccccssssssseseeeees 34 Band Saw Process Flow Diagram (Part 2). ...........::::::esssesesseeeeeeeees 35 Band Saw Process Flow Diagram (Part 3). ..............cccccceceeseneteeeeees 36 Sources of Information for the RCM. ................cccccesssseeeeeeeeeeeeeteseees 47 Eliminating Production Constraints. ..................ccccccccesesseseeeeeeneeenees 50 Classification Decision Logic for ROM Il. ...............ccceeeeeeeeeeeeeeeees 56 Maintenance Task Decision Logic for Safety/Environmental ae ee 61

Maintenance Task Decision Logic for Operational Failures........... 62 Maintenance Task Decision Logic for Nonoperational Failures. ....63 MIL-STD-2173(AS) RCM Decision Logic. ..............ccceeeeceeeeceeeeeeeeees 81 AMC-P-750-2 RCM Decision LogIc. ..............::::s:eeeeeeeeeeeeeteeeeereeeeees 82 MSG-3 RCM Decision LOGIC..............cccccccsseeeeeeeceeeeseeeesneaeeseseeesees 83 RCM II Decision LOGIC. ..............ccccccccceesececseeeceeeeseeceeseeaeeesseeeeeteees 84

Structural Significant Item Decision LOgIc. .................cccccseeeeeeeeeeeees 85 Sources of Information for the MTA...............cccccccccscssssssssseseeseeeetees 87

vi

List of Tables

Table 1. The Big Six LOSSES. ...............cccccceccccesssecceceaeeeeeeaaeeccesauseeceeaueeeeesaaeneees 14 Table 2. Processor Utilization Profile. ..................cccccccccseseeceeeesneeeseerecessaenaeeeees 19 Table 3. Functional Allocation to Process FIOWS. ...............ccccccsssseeeeeeeeneeeeeeees 37 Table 4. Band Saw PFMEA (Part 1). ...........ccccccccccccccecceceeeeeeeseeseetereeeneeeeeeneceess 41 Table 4. Band Saw PFMEA (Part 2). 20.0.0... ...cccccceceeceeeeeeeeeceeeaeneeeeseeesenateesens 42 Table 4. Band Saw PFMEA (Patt 3). .............cccccccccecescececeeeeececceceeeeeesseseeeneneeees 43 Table 5. Band Saw Annual Maintenance Costs (Part 1)..............ccccceccseeeeeeees 44 Table 5. Band Saw Annual Maintenance Costs (Part 2)...................::cceeeee 44 Table 6. Maintenance Cost Breakdown. .................ccccccsssseececceseeeeeeeeeeeeeseseeeeees 46 Table 7. Default Actions. ..............:cccccccccccessseeseenseeeseaeeeeecaueseeseaeaeeessaaeeeeseeaaeeees 55

Table 8. Manufacturer Recommended Maintenance Tasks. ..................::006 58 Table 9. Alternative Maintenance TaskS. .................cccccsssseeceeseceeceteeeeeneaneeeenees 69

Table 10. Proposed Maintenance Plan (Part 1)... cccccsssseeeeesseeeeeeeeee 72 Table 10. Proposed Maintenance Plan (Part 2).............ccccccccccsccssseresessseseeeeeees 73 Table 10. Proposed Maintenance Plan (Part 3)................eeee eeesseseeeeeeeeeeteeeeees 74 Table 10. Proposed Maintenance Plan (Part 4)................:cccccescceeeeseesseeeeeeenees 75 Table 11. Band Saw Annual Preventive Maintenance Costs..................::008 76 Table 12. Preventive Maintenance Plan Summary. ..................::c::::ssceeeeeeeeeeees 78 Table 13. Maintenance Task Analysis (Sheet 1). .............ccccsseeeseeeeeeeeeeeeeeees 88 Table 14. Maintenance Task Analysis (Sheet 2). .................:cccccccsseeeeeeeeereeeeees 89

Vii

1.0 Introduction

1.1 Identification of Opportunity

To remain competitive, organizations are attempting to simultaneously

reduce operational costs, increase throughput, and enhance product and

service quality. A cost category which significantly impacts all of these

attributes is manufacturing system maintenance.

With most modern manufacturing systems increasing in complexity,

maintenance requirements have become more significant and demanding.

Manufacturing system maintenance often has a sizable impact on an

organization's profitability, and consequently, it's competitiveness. According

to a study reported by R. K. Mobley, maintenance activities are responsible for

15% to 40%, with an average of 28%, of the total cost of finished goods."

Presently, technological advancements and a growing transition towards

automation are likely to create a system more dependent on maintenance. "T.

Wireman reports from a study conducted in 1989 that the estimated cost of

maintenance for a selected group of companies increased from $200 billion in

1979 to $600 billion in 1989." 2:5

Many manufacturers are faced with increasing customer demand and

shrinking resource availability. To meet production demand, the manufacturing

system must sustain the highest throughput possible. Consider the Just-in-

Time procedures and transfer lines becoming prevalent in many industries

such as the automobile industry. Downtime at one point in the manufacturing

system results in downtime for every process. At GM's East German

1 Mobley, R. K., Introduction to Predictive Maintenance, Van Nostrand Reinhold, New York,

1990. 2 Wireman, T., World Class Maintenance Management, Industrial Press, Inc., New York, 1990. 3 Titan Software Corporation, "Maintenance: Profit Center 2000," Plant Engineering, March

1992, pp. 101-112.

automobile assembly plant in Eisenach, downtime at one process resulted in

1,840 idle workers.* Any loss in throughput results in a loss of opportunity to

fulfill demand. Maintenance must be effective and responsive to meet

manufacturing system demands.

United States industry loses about $66 billion annually on unnecessary

maintenance of plant and equipment.5 To meet the need of high-tech support,

eliminate unnecessary maintenance, and control rising maintenance costs,

computerized maintenance management systems (CMMS) were introduced in

the early 1980s. A CMMS utilizes computers and technological advances to

assist with the management and execution of the maintenance program.

CMMS users list primary benefits of increased manufacturing asset

productivity, increased maintenance productivity, and decreased material

costs. However, these systems are not based on a methodology for

determining maintenance plan requirements. A CMMS cannot solve

maintenance problems that come from a poor maintenance philosophy. The

most successful implementations of a CMMS build on an existing framework of

sound maintenance philosophy, good maintenance practices, organization and

documentation of tasks, and an integrative equipment history.’

1.2 The Objective of the Project

The objective of this project is to describe and apply an approach to

developing a cost-effective maintenance plan to support the manufacturing

4 Hamrick, James. "Eastward With TPM and CMMS," Industrial Engineering, October 1994, pp. 17-18.

5 Maquire, Micheal, "Predictive Maintenance: What does it do?," Electrical World, Vol. 206 No. 6 June 1992, pp.11-12.

8 Titan Software Corporation, "Plant Maintenance As Profit Center: Rethinking Our Priorities," Plant Engineering, 1991 Encyclopedia, July 1991, pp. 228-230.

’ Titan Software Corporation, "How to Select and Get the Most From a CMMS," Plant Engineering, 1991 Encyclopedia, July 1991, pp. 233-235.

system of an organization. The approach should be applicable to: (1) assess

each process alternative in a life-cycle design decision in terms of operation

and maintenance requirements, (2) optimize the operation and maintenance

costs for existing manufacturing systems, and (3) provide a means of

continuously assessing and improving the maintenance plan as_ the

manufacturing system and its environment changes.

This project will describe the methodology for developing a maintenance

plan as applied to an existing manufacturing system. The decision

methodology will be applied to the Amada HFA-330 band saw in service at

Nautilus International.

This approach translates into the optimization of present and future

operation and maintenance costs. For an existing system, the first cost

associated with planning and purchasing the manufacturing system has

occurred. Regardless of whether the manufacturing system was designed for

optimal total life-cycle cost, management must consider further optimization of

the system’s operation and maintenance costs as the system’s environment

changes. Manufacturing management's attempt to further improve the system

will only affect present and future costs, not sunk costs. The decision

methodology's place in the overall optimal alternative selection process during

manufacturing systems design will be addressed in the last chapter.

This project will not invent the methodology or procedure used to

develop the maintenance plan. This project will apply existing methods

together to develop the maintenance plan. Specifically, the information within

the manufacturing system needed to develop such maintenance plans must be

identified, collected, documented, and maintained to justify a course of action.

This project will identify information sources needed for the decision logic,

identify the information’s path through the decision logic, show how the

decision logic thoroughly documents decision justification, and relate the

information to its effect on the end-result maintenance decision.

The Process Failure Modes and Effects Analysis (PFMEA) and the

Reliability-Centered Maintenance (RCM) analysis can be used in tandem as a

decision logic to develop a cost-effective maintenance plan. The PFMEA will

allow a user to map and document the manufacturing process, the failure

mode-cause sequences, and the cost of each failure. The RCM decision logic

will be used to determine the most appropriate maintenance tasks based on the

information provided by the PFMEA. A Maintenance Task Analysis (MTA) may

be used to analyze and cost the feasibility of maintenance tasks.

The PFMEA is a simple, systematic tool which identifies, quantifies, and

prioritizes system weaknesses. The PFMEA can be tailored to suit the

analyst's needs and capabilities. The PFMEA provides a powerful input to an

RCM analysis. The RCM analysis provides a structured and formal decision

logic that assists an analyst in translating PFMEA output into a effective and

justifiable maintenance plan. The RCM analysis decision logic can be tailored

to reflect the capabilities of individual manufacturing facilities and personnel.

After using the tools successively, the analyst should have countered all failure

causes with either preventive maintenance task(s), corrective maintenance

task(s), or a redesign or adjustment of the system.

Although both are intended as tools for systems design improvements

and advanced product quality planning, these analyses are easily applied to

existing systems. Both tools provide a means of continually assessing a

system and providing feedback for continuous improvement. After an iteration

of improvement, the manufacturing system or the manner in which it will be

operated will change. These changes, in turn, should be reflected in the next

iteration of the PFMEA and RCM analysis in order to identify and reprioritize

system constraints. See Figure 1.

Process Data, Process Data, Failure Data, Failure Data,

| Maintenance Task PFMEA Maintenance Task _—sif | Analysis Analysis

| Failure Data

RCM Maintenance Task ——\ Analysis

q

1

|

Preventive Corrective Redesign | Maintenance Maintenance and/or

Plan Plan Improvement

Process & Failure

Data Collection

Figure 1. The PFMEA-RCM Relationship with a Feedback Loop.

Manufacturing facilities are searching for means of increasing market

posture and securing profit. The PFMEA and RCM analysis provides a means

of identifying opportunities to meet these goals. These tools will identify

production system constraints and allow the manufacturing organization to

attack them.

2. will failure

assessment, and define parameters of the manufacturing system under

Chapter discuss manufacturing systems, failure,

analysis. Chapter 3 will discuss the PFMEA and its application to the

manufacturing system under analysis. Chapter 4 will discuss the RCM analysis

and its application to the manufacturing system under analysis. Chapter 5 will

summarize the results of the maintenance plan formed through the use of both

analysis.

2.0 Manufacturing Systems Background

A manufacturing system is a group of processors and material handlers

in a configuration consisting of serial and/or parallel relationships which

converts raw materials into a product which the company intends to sell for a

profit. The functions that a manufacturing system is intended to perform are

provided in the forms of technical drawings, bills-of-materials, process plans,

routings, process instructions, and work instructions. These items convey to

manufacturing the product functions desired by the manufacturer's customers

and the process by which it will be made. Processors within the manufacturing

system impart those specifications onto the finished product.

Throughput, inventory, and operational expense are three major

measures of a manufacturing system. Throughput is the rate at which the

system generates money through sales. Inventory is the money that the

system has invested in purchasing things which it intends to sell. Operational

expense is the money the system spends in order to turn inventory into

throughput.2 In order to maximize company profitability, throughput must be

increased while inventory and operation expense are decreased. Mechanical

resources (ultimately money) typically constrain throughput. A company's cash

flow constrains inventory and operational expenditures.

A bottleneck is the processor which dictates the throughput of the

manufacturing system. Utilizing a processor upstream of the bottleneck in

excess of the bottleneck throughput creates inventory and does not increase

the output of the manufacturing system. Processes downstream can only

process at the rate at which the bottleneck supplies work-in-process.

Downtime at a processor within the system results in a throughput loss only

when that processor is or becomes the bottleneck of the system.

8 Goldratt, Eliyahu and Jeff Cox. The Goal: A Process of Ongoing Improvement, Second Edition, North River Press, Croton-on-Hudson, NY, 1992.

An illustration of the throughput constraints for five processors in series

is shown in Figure 2. The X axis of the graph represents the processor and the

Y axis represents each processor's production rate (units per time period) for

four utilization profiles. The utilization profiles are denoted in the graph legend.

For example, Processor 1 is used to produce 60 units per period. Processor 1

does not lose any units to scrap. It loses 5 units per period to down time and it

has an unused capacity of 40 units per period. Processor 3 is the bottleneck of

the system. The maximum capacity of Processor 3 is 70 Units. Processor 3

loses 10 units per time period to down time and 6 units to scrap. Processor 3

has a throughput of 54 units per time period. (70 - 10 - 6 = 54). Since

Processor 3 is only supplying a rate of 54 units to Processor 4, Processor 4

cannot exceed a rate of 54 units. Any scrap at Processor 4 reduces the rate at

which it can supply Processor 5. Therefore, system throughput is equal to the

bottleneck processor throughput less all scrap generated by downstream

processes. Throughput for a manufacturing processor X is:

Throughput(X) = Capacity(X) - Scrap(X) - Down Time(X) - Unused Capacity(X)

where:

X = the processor's precedence in a serial relationship of n processors,

Capacity(X) = actual capacity of processor X in units,

Scrap(X) = units lost when processor X produces nonconforming parts,

Down Time(X) = the down time of processor X in units, and

Unused Capacity(X) = unused capacity of processor X in units,

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Throughput for a system of n manufacturing processors in series is:

System Throughput =Min( >) Throughput(X,Y)) y Scrap(X)), Y

where:

Y represents the quantity of processor X in parallel, and

b signifies the bottleneck processor, Min(” Thru(X,Y)). ¥

The bottleneck process, being responsible for system throughput

limitations, may be the most crucial system element to maintain. However,

pinpointing bottlenecks in a well-balanced system or a job shop with a diverse

product mix presents a challenge. Equipment failure, setups and adjustment,

idling and minor stoppages, reduced operational speeds, process defects, and

reduced yield 9 can cause a bottleneck to shift to other processes.

Manufacturing management has the responsibility of allocating

operational expense, which is a limited resource, to sustain system throughput.

Manufacturing management requires a means of identifying and prioritizing

system failures. The FMEA will fulfill that function, allowing manufacturing

management to focus operational expenditures wisely. This will insure that the

organization obtains the largest return on investment of their limited resource.

2.1 The Nature of Failure

A failure is the condition in which a system is unable to perform its

intended function.1° In the course of failure, a component in the system may

exhibit physical conditions of degradation and imminent failure.

9 Nakajima, Seiichi. Introduction to Total Productive Maintenance, Productivity Press, Cambridge MA, 1988.

10 Blanchard, B.S., Verma, D. and Elmer L. Peterson. Maintainability. A Key to Effective Serviceability and Maintenance Management. John Wiley & Sons, Inc. New York, New York, 1995.

10

Vibration, heat, or odors unusual to normal process baselines may

indicate that a potential failure (P) is about to occur. Examples of signs of

potential failures would be increased temperature in gearboxes, low fluid

levels, or increased vibration in bearings. Eventually, functional failure (F)

occurs. The elapsed time between signs of potential failure (P) and functional

failure (F) is known as the P-F interval. See Figure 3.

Conditio

n ——»

Time ——> F

Figure 3. Component P-F Interval."

Component reliability can be represented by a reliability curve as shown

in Figure 4. Some failures can be related to component age (as in Figure 4,

Curves A, B, and C.) Age-related failures result from component wear which

occurs during operation. Wear usually occurs when adjoining surfaces mate

and rub each other. Systems or components showing age-related failure would

be granulators, brakes, clutches, and tires. Wear associated with age-related

failure may be detectable if there is accessibility to the component.

Given comparable care, identical components exhibiting age-related

failure tend to fail around the same age, or life. In the event that a component

shows signs of aging, on-condition monitoring techniques may be able to

detect potential failure (P). The ability to establish a usable life for the

11 Moubray, John. Reliability-centered Maintenance II. Industrial Press, Inc., New York, NY, 1992.

11

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Figure 4. Reliability Profiles.

12

component allows maintenance to possibly schedule restoration or discard

tasks.

Not ail failures are age-related. (See Figure 4, Curves D, E and F.)

Typically electronics, hydraulics, pneumatics, and rolling element bearing do

not fail as a function of age. 12 Since there is not a useful life associated with

these items, personnel must be able to detect potential failure (P) through

some on-condition task or allow the component to fail.

Failure can occur either sporadically or chronically. Chronic failures

occur persistently and are usually a reflection of the processor's inherent

capabilities, condition, or management philosophy. The cause-and-effect

relationship associated with chronic failures is difficult to establish. Sporadic

failures are sudden changes in operating conditions which have a

straightforward cause-and-effect relationship. These failures can typically be

easily corrected by restoring the cause to its original condition. Tool wear and

the movement of adjustable processor parameters are sometimes responsible

for sporadic failure. Physical feed stops on a manual processor would be an

example of an adjustable processor parameter. They may slip after a period of

use.

Failure can be either equipment failure or function-related failure.

Equipment failure is the failure of the processor to produce conforming parts at

the standard processor operational rate. Function-related failure is the failure

of the processor or its tooling to impart its intended engineering specification or

function onto the part. Function-related failure is a function of required

engineering specifications as well as inherent processor capabilities. For

example, a band saw may have a process capability of +0.003 inches.

Although the saw can operationally perform all week, as the blade wears the

saws capabilities will fall to + 0.008 inches. Company A may use the saw to

12 Moubray, John. P. 116.

13

fulfill engineering tolerances of +0.015 inches. As the blade wears,

engineering specifications will not be compromised. In fact, the blade may dull

to the point that the saw cannot sustain the standard operational rate, hence

operational failure. Company B may use the saw to fulfill engineering

tolerances of +0.005 inches. As the blade wears, engineering specifications

will be compromised at some point in use. This will result in nonconforming

product or function-related failure. Thus, the same processor may have

different operational or utilization profiles which may create a different

maintenance requirement.

2.2 Failure Assessment Through Effectiveness Measures

Manufacturing system failure is best defined by the “Six Big Losses.” 15

These losses, listed in Table 1, are categorized into downtime, speed losses,

and defects.

Table 1. The Big Six Losses.

Downtime:

1. Equipment Failure

2. Setup and Adjustment

Speed Losses:

3. Idling and Minor Stoppages

4. Reduced Speed

Defects:

5. Process Defects

6. Reduced Yield

13Nakajima, Seiichi. Introduction to Total Productive Maintenance, Productivity Press, Cambridge MA, 1988.

14

Downtime losses include processor lost time to (1) equipment failure

from breakdown and (2) lost time due to processor setup and adjustment.

Availability or uptime of the processor is defined as follows:

Available Time - Downtime Availability = vanapuny Available Time

The measure of availability penalizes a manufacturing organization for having

an idle processor. It would not be proper to evaluate processor availability

outside the processor’s scheduled use.

Speed losses include (3) idling and minor stoppages due to sporadic

problems and (4) reduced processor speed. Within the availability of the

processor, manufacturing personnel must fully utilize the processor.

Production efficiency is defined as follows:

Standard Cycle Time x Qty Processed Production Efficiency = Operating Time

Defect losses are (5) process defects and (6) reduced yield. Reduced

yield refers to any loss of parts that may result from a setup or adjustment of

the processor for the upcoming lot. In the context of manufacturing, these two

losses are one in the same: a nonconforming part. The quality rate is defined

as follows:

Processed Amount - Scrapped Amount Quality Rate =

y Processed Amount

15

Overall Equipment Effectiveness (OEE) is a product of availability,

processor efficiency, and scrap rate. The OEE is the product of the three

because scrap rate is a function of processor efficiency and processor

efficiency is a function of processor availability.

OEE = Availability x Processor Efficiency x Quality Rate

Mean Time Between Failures (MTBF) is an effectiveness measure that

will provide a failure rate for a processor. The failure rate will allow the

calculation of expected downtime over a period of time and its cost. The MTBF

is defined as follows:

Total Operating Hours

Number of Failures MTBF =

Mean Time to Repair (MTTR) is an effectiveness measure that will

provide the amount of time needed to repair a failure. This measure will be

used to cost corrective maintenance labor, lost operational labor, and estimate

average corrective maintenance down time. The MTTR is defined as follows:

Total Maintenance Hours

Number of Failures MTTR =

2.3. Failure Assessment Through Cost Measures.

OEE as an overall benchmark measurement of a process or

manufacturing system may not suffice, alone. Throughput like OEE is a

function of availability, processor efficiency, and quality rate. There is a cost

associated with sustaining the desired throughput of the processor or

16

manufacturing system. The cost associated with sustaining the desired level of

availability, processor efficiency, and quality rate is simply all operational and

maintenance costs charged to the processor, or operational expenditures as

defined by Goldratt. Availability, processor efficiency, and quality rate can

contribute to a loss of throughput and therefore a possible loss of opportunity

to gain profit. When external market demand exceeds system throughput,

nonproduction time at a processor results in a loss of opportunity.

To determine the cost associated with the lack of capacity, the external

demand, processor capacity, and system capacity must be determined. The

cost of lost opportunity associated with the lack of capacity is a measure of the

profit forfeited from the unfulfilled demand that the system could have satisfied.

Cost of Lost Opportunity =

Profit Margin Per Unit x (Demand - System Throughput)

The production of nonconforming product not only lessens system

throughput. It creates an additional cost in the form of scrapped material or

additional labor to reclaim the material. Scrap cost includes the cost of lost

material, labor, and overhead. Rework cost includes the additional cost of

labor and overhead. The cost of the functional failure may provide incentive to

counteract the cause of failure prior to its occurrence.

F

Scrap Cost = Material Cost + >’ (Labor Cost + Overhead Cost) 1

where F signifies the failing processor in the series of processors.

Rework Cost = Rework Labor Cost + Overhead Cost

17

Each product will have a separate scrap or rework cost associated with it

which is dependent on the processor needed for rework and the nonconforming

attribute.

There is a cost associated with corrective and preventive maintenance

of the system. These costs include cost of replacement parts, consumables,

and cost of maintenance labor.

2.4 Defining the Manufacturing System

The processing line studied for this project consists of 1 Amada HFA-

330 band saw, 3 Okuma LNC8 CNC lathes, and 2 Eaton-Leonard CNC

bending machines. See Figure 5. The multiples of each processor function in

parallel to each other. At Nautilus, the band saw is used to cut raw stock to

length. The lathe is used to reduce outer diameters or produce inner

diameters. The bending machine is used to create bends in material. This

project will focus on the Amada HFA-330 band saw.

m= Lathe 1 J

— Bender 1

— Saw 1 Lathe 2 |

Bender Oe 2

! Lathe 3 — Figure 5. Manufacturing System Process Flow.

Actual information regarding Nautilus’ machine utilization, part

specifications, process parameters, and product costing are not available for

18

use in this project.14 Reasonable values for these parameters are used for the

purpose of performing the analyses which is the focus of this project.

Processors operate 24 hours per day with exceptions for preventive

maintenance, tooling adjustments, breaks, and lunch. The utilization profile of

each processor is given in Table 2. Preventive maintenance performed during

the scheduled time is performed by the operator as part of an autonomous

maintenance program aimed at extending processor life and product quality.

These autonomous maintenance items will be discussed during the RCM

analysis. Corrective maintenance is the average time lost to the processor per

day as a result of tooling adjustments and failure. Tooling adjustments are

required to prevent function-related failure. Tooling adjustments are usually

triggered by trends in SPC data.

Table 2. Processor Utilization Profile.

Processor Saw Lathe Bender Processor Quantity 1 3 2 Standard (Min / Pc) 0.33 3.00 1.50 Output Capability per Hour Uptime (Pcs) 180 60 80 Processor Availability Per Day (Min) 1,440 4,320 2,880

Scheduled Down Time (Min) 180 270 130 Unscheduled Down Time (Min) 13 15 20 Scrap per Day (Pcs) 5 15 24 Processor Time Lost to Scrap (Min) 2 45 38 Available Processing Time (Min) 1,245 3,990 2,692

Output Capability per Day (Pcs) 3,772 1,330 1,794 Demand (Pcs) 1,330 1,330 1,330 Demand (Min) 439 3,990 1,995 Excess Capacity (Pcs) 2,442 0 464

Excess Capacity (Min) 805 0 696

14Most of the information required for the analyses was not collected by Nautilus therefore the data was unavailable. Information that was available is proprietary to Nautilus International and is not intended for public knowledge.

19

All processors have excess capacity except for the CNC lathes. The

cost of lost opportunity associated with the production system can be

calculated by determining profit lost for every hour it is not performing

productive work. The average profit margin per part is $5.20. For every hour

that the system loses throughput, the company loses $306.80 in profit. System

throughput is the throughput of the lathe less the loss of throughput due to

scrap at the bender.

(60 - 1) Parts / Hour * $5.20 / Part = $306.80 / Hour

For non-bottleneck processors, the lost opportunity cost will only be

applicable when production time cannot satisfy demand. Although the saw is

not a bottleneck processor, a failure or combination of failures that exceeds

over 805 minutes of downtime per day would reduce saw production time and

create a loss of opportunity.

Scrap results from functional failure of processors. Scrap not only

wastes production time but creates a loss of material, labor, and overhead. For

this project, the average part cost of $26 will be used as the scrap cost.

Rework is not an option.

There will not be costs associated with contractual breach, loss of

customer faith, or personnel injury. The method by which these costs are

derived may differ based on the manufacturing facility and the management

philosophy.

Nautilus only keeps spare components for consumable items. These

items are saw blades, wire brushes, lubricants, and fluids. Parts are usually

available overnight from California. Additional down time due to shipping spare

parts will be 15 hours.

20

3.0 Process Failure Modes and Effects Analysis (PFMEA)

3.1 Introduction

A Failure Modes and Effects Analysis is a systematic method of

identifying failure modes, their frequency of occurrence, their causes, and their

effects within a system. The FMEA provides a logical review of the system to

determine which failures are most critical, which failures will result in hazardous

conditions for personnel, and which failures result in products that do not meet

specifications. This enables a company to identify, document, and address the

most critical production problems using limited capital resources. 15

A FMEA is an iterative and continuous analysis, and can be performed

during design, after production, on a product, or on a process. FMEA is most

effective when performed during design in order to identify and implement a

cost-effective design alternative. This analysis can improve preventive

maintenance plans, control plans, and safety procedures. The FMEA will guide

an analyst in determining the severity of a system failure, which may serve as a

ceiling to preventive maintenance costs during maintenance design.

In order to increase throughput (and consequently sales) processor

rates and scrap rates must be improved. A completed FMEA will identify those

items that reduce system efficiency. The contributors can then be addressed

through redesign or maintenance to allow the system to achieve the maximum

throughput gain at the lowest expense. Manufacturing system improvements

will not only result in an increase in throughput by decreasing downtime and

scrap; it may increase personnel safety and increase product quality.

The FMEA can be a design FMEA (product) or a process FMEA. A

FMEA consists of six major steps: (1) define the system, (2) allocate system

154 FMEA is essentially the same as a FMECA, except the FMEA does not utilize the criticality analysis. There is a process FMEA (PFMEA) and a design FMEA (DFMEA).

21

requirements to system components, (3) analyze the failure modes, effects,

and causes of the system, (4) identify the means of failure detection, isolation,

and compensation, (5) determine the severity/criticality of each sequence, and

(6) take action as indicated by analysis results in the form of redesign,

preventive action, and/or corrective action to control or eliminate risks

associated with failure.

The FMEA has been used with qualitative and/or quantitative input. The

type of input depends on the system's life cycle phase, the availability of

pertinent information, the availability of resources to perform the analysis, or

the desired accuracy of the analysis. A system in the design phase may have

no historical data or component libraries from which to derive quantitative data.

Established systems may have sufficient historical data which supports

confident quantitative input. Qualitative input is generally quicker and easier to

collect. Qualitative input relies primarily on the experience of people within the

manufacturing organization. Figure 6 diagrams information sources and

information flow through the FMEA.

The Department of Defense requires the performance of a FMECA on

system and equipment acquisitions. Many agencies within the federal

government as well as the military divisions frequently use the FMECA as an

analysis and feedback tool for systems hardware design. '®

The Surry Nuclear Power Plant uses the FMEA as an operational

improvement tool to troubleshoot and prevent the reoccurrence of failures. The

failure mode's level of severity dictates the extent of detail that is used during

the analysis. A non operational failure will receive a shallow analysis while an

operational failure will receive a full analysis.”

16 Borgovini, R., Pemberton, S., and D. Russell. “Failure Mode, Effects, and Criticality Analysis (FMECA),” Reliability Analysis Center, Rome, NY operated by IIT Research Institutue, 1992.

17 Collin Bruce, Associate Engineer, Safety Department, Surry Nuclear Power Plant. Personal Interview.

22

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Companies are using the FMEA to analyze product designs before

introducing them to market. Chrysler Corporation, Ford Motor Company, and

General Motors Corporation issued an instruction manual in February 1993 by

which they and their suppliers perform both product and process FMEAs.'®

The procedures as listed by the FMEA instruction manual are excellent with the

exception of its complete qualitative nature. Severity, occurrence, and

detection are measures based on scales of one to ten. Although these

automotive firms may find this sufficient, this does not provide a basis by which

to perform a break-even analysis or cost justification of redesign, preventive

actions, or corrective actions.

The FMEA is also being used as a process improvement tool. The

PFMEA is used to map the manufacturing process, identify failures, and assess

their severity. Performing a pareto analysis on the PFMEA results will identify

the areas with the highest opportunity for improvement. The company can

make efficient use of its resources by resolving the highest ranking problems.

See Figure 7.

Federal Mogul Corporation of Blacksburg has recently began the use of

the PFMEA to improve process integrity and part quality. The PFMEA has

been used to identify and prioritize failure causes so the company could attack

them as resources allowed. The PFMEA was tailored to suit the manufacturing

plant's intent of process improvement and assurance to customers of their

commitment to quality. The PFMEA procedures that Federal Mogul developed

with the assistance of the Systems Engineering Design Laboratory at Virginia

Tech are heavily based on those developed by The Big Three with a minor

influence by MIL-STD1629A.‘9

18 Chrysler Corporation, Ford Motor Company, General Motors Corporation, Reference Manual, Potential Failure Mode and Effects Analysis (FMEAA), Second Edition, February

1995. 19 Verma, D. and B. Bowen, Process FMEA Training Manual, Federal Mogul Corporation,

Blacksburg, Virginia 24060. December 1992.

24

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25

There have been many computer programs designed to facilitate the

execution, information handling, and documentation associated with a FMEA.

FailMode, Failure Modes & Effects, PC - FMECA, Relex FMECA, and CARA

FMECA are five programs which perform a hardware FMEA based on MIL-

STD-1629A. Some of the programs support MIL-STD-338 and MIL-HDBK-217.

Most of these programs provide libraries of historic, quantitative figures-of-merit

for electronics and commonly-used components. These libraries help build a

reliable analysis output. FMEAPlus is a Windows-based software developed to

support the FMEA format developed by The Big Three.”

Given that the FMEA successfully identifies opportunities for

improvement, a methodology will be necessary to determine effective actions

which are responsive to those opportunities. The RCM analysis (along with a

Maintenance Task Analysis) will be used to identify effective and cost-justified

actions which will capitalize on the opportunities presented by the FMEA.

3.2 PFMEA Methodology

System requirements are process or product parameters that define the

desired results of the process. Customer specifications through Quality

Functional Deployment or engineering design documents usually provide the

system requirements. Most of the system requirements fulfill customer

requirements, while others may provide functionality to downstream processes.

A functional flow diagram is a flow chart of the process. It defines the

sequence of operations that need to be performed in order to achieve the

desired outcomes of the overall process. The functional flow diagram should

reflect quality checks, work-in-process, and other non-value added processes.

These diagrams are prepared to the detail necessary to establish an

20 See Appendix C for software references.

26

understanding of the process. The functional flow diagram can be developed

from process plans or part routings. Further, the functional flow can be

developed or validated by performing a "walk-through." During a “walk-

through," the analyst traces the steps of a part through the manufacturing plant

noting all processes, inspections, transits, and points of storage. At this point

in the analysis, the entire system should be defined.

The system requirements are then allocated to their respective

operations. If an operation can affect a requirement, the requirement is

allocated to that operation. Process plans, product routings, and "walk-

throughs" will assist the analyst with allocating system requirements.

A failure mode is defined as the inability to achieve a system

requirement. Failure modes throughout the process can be determined by

experienced operators, maintenance history, manufacturer documentation, and

quality assurance history.

A failure cause is defined as a mechanism by which the process can

experience a failure mode. Failure causes can be determined through

manufacturer documentation, Fault Tree Analysis, or experimentation.

Maintenance data may provide insight into failure causes. Quality assurance

data may provide insight into quality problems or provide a trace to root

causes.

The effect of a failure can be defined as the consequence of the failure

mode-cause sequence. External effects are effects to the customer. Internal

effects are effects to the failed process and processes down stream. Internal

effects have a relatively concrete cost whereas external effects have a cost that

is more difficult to estimate. Failure effects can be determined by the analyst’s

experience, maintenance history, or quality assurance history. At this point in

the analysis, all likely failure modes of the system has been documented.

27

Current controls are operations or process procedures that are intended

to prevent a certain effect from occurring or propagating down stream.

Examples of current controls are quality control checks, machine vision

cameras, or misprogression sensors.

The next step in the FMEA process is to determine the frequency of

occurrence, the severity of the effect, and the ability to detect the effect for

each mode-cause-effect sequence. This information will provide the severity or

cost of each failure-mode-cause sequence. To assist in the goal of developing

a cost-justified maintenance plan, these measures should be quantitative, not

qualitative. The cost of each sequence will provide the extent to which process

improvement or preventive maintenance can be justified.

Occurrence is the frequency of occurrence. Severity is the cost of

failure measured in terms of safety, quality, reputation, lost production time,

and maintenance cost. Detection is the probability that the current control will

detect the failure mode-cause-effect sequence before it causes any damage.

This measure will determine how frequently and to what extent that the severity

cost will be incurred upon failure.

A Risk Priority Number is a measure of the criticality of a failure mode-

cause-effect sequence. RPNs are the product of the relevant occurrence,

severity, and detection ratings according to The Big Three procedures. The

RPN in the context of this project will be the annualized cost of failure. For

example, a machine fails five times per year at a cost of $1,000 per failure.

Controls can preempt 50% of the costs associated with four out of five failures.

The failure sequence would cost $3,000 per year.

$1,000 / failure * 5 failures / year * (1 - (50%) * (80%)) = $3,000

28

Performing a pareto analysis of the failure costs will prioritize efforts and

resources where they can best be spent to improve system costs throughput.

The PFMEA supports the maintenance development process by

performing a formal analysis of failure modes, frequencies, causes, and effects

of the system. Further, the analysis will guide the analyst in determining the

cost of allowing a failure sequence to occur. This information is ultimately

useful when justifying process improvements or preventive maintenance

actions.

The PFMEA supports the goal of continuous improvement by increasing

the knowledge of the process so that items in need of greatest attention are

corrected. The PFMEA is an iterative process. As more reliable information

emerges from the manufacturing system or problems are reduced, the PFMEA

should be updated. These changes in the system may change the priorities of

other failure causes or create new failure modes.

3.3 PFMEA Example

The analyses demonstrated in this project will be performed on the

Amada horizontal band saw Model HFA-330. The band saw accepts any

length raw stock. It can be programmed to index and cut up to 99 different cut

lengths of any quantity from the stock. Through the use of an encoder and

hydraulics, the band saw will index and measure the programmed cut length,

then cut the stock. It will continue to index to the programmed length and cut

until the saw uses up the material or finishes the programmed lengths and

quantities. The Amada band saw is equipped with numerous system fault

detection and safety features that will automatically stop the sawing process.

29

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Most part requirements are specified to manufacturing in the form of a

part drawing. Part drawings specify the desired features and tolerances of the

part. A manufacturing process plan and routing is created based on these

desired features and tolerances. Part drawings are usually stored is a central

location by Quality Assurance. This project will focus on the production of an

incline press movement arm. See Figure 9.

The print shows a part made of two-inch diameter 1040 cold-rolled round

stock that must be five feet long with + 0.015 inches tolerance. Eight inches of

one end of this stock must have the outer diameter reduced to one inch in

diameter + 0.001 inches tolerance. The piece of stock must receive two (2)

ninety degree bends in the same plane + 0.5°.

3.5 Defining the Process Flow

Process flows are represented by part routings and by process flow

diagrams. The processor required to perform the desired part specifications is

selected by its ability to perform the function and its ability to meet required

tolerances. Machine abilities are usually defined by the manufacturer in

purchasing specifications. Process capability studies can further determine

machine capabilities given the variables on the shop floor. All machines are

capable of the parts manufacturing requirements. The Amada manual

indicates that the machine is capable of repeating 0.001 inch increments.22

This author's experience is that the Amada band saw is capable of holding

0.003 inches.

22 Amada. “Horizontal Bandsaw HA-330/HFA-330 Operator's Manual.”

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The part must first be cut from eight foot stock to five feet. The stock

must then be lathed to achieve the smaller outer diameter. Last, the part is

bent in both places using the CNC bender.

The band saw will be responsible for indexing the part to the proper cut

length and cutting the part to tolerances. Additionally, the saw will flood the

blade with coolant. The coolant will maintain blade life, extending the saws

capability to maintain desired tolerances. The coolant will also rinse metal

chips from the cutting area so that the blade does not bind or cut out-of-square.

The process flow diagram for the band saw functions is in Figure 10.

3.6 Functional Allocation

At this point, the desired part features must be assigned to process

functions which effect the ability to meet the desired features. To do this, the

analyst must understand the process flow, the manufacturing processor, and

the part manufactured. The saw has two functions: (1) index the part and (2)

saw to specification. The results of functional allocation are in Table 3.

3.7 Defining Failure Modes

Failure modes are failures to achieve the desired system requirements

or outcomes. The failure modes for the outcomes in Table 3 are (1) part length

not indexed and (2) stock not sawed to proper specification. The column titled

“Failure Mode” in Table 4 (Part 1) will list potential failure modes for process

descriptions associated with the band saw.

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Table 3. Functional Allocation to Process Flows.

Process Flow Outcome Retract Rear Vice Desired Part Length Indexed Rear Vice Clamps Raw Stock Desired Part Length Indexed; Desired

Raw Stock Dimensions Rear Vice Indexes Raw Stock Desired Part Length Indexed

Front Vice Clamps Raw Stock Stock Sawed to Proper Specification Saw Part Stock Sawed to Proper Specification Lower Saw Head Stock Sawed to Proper Specification Rotate Saw Head Stock Sawed to Proper Specification Raise Saw Head Stock Sawed to Proper Specification Pump/Flood Coolant Stock Sawed to Proper Specification Filter Coolant Stock Sawed to Proper Specification Convey Chips Stock Sawed to Proper Specification Brush Blade Stock Sawed to Proper Specification

3.8 Defining Failure Causes

Each failure mode is caused by the failure of a part or parts of the

system. As system components wear, they may fail, causing the entire

processor to fail. The column titled “Failure Cause” in Table 4 (Part 1) will list

potential failure causes for process descriptions associated with the band saw.

3.9 Defining Failure Effects

The effect of the failure is the consequence of the failure mode-cause

sequence. The effects of failure could be reduced process throughput, scrap

parts, rework costs, tooling damage at subsequent processes, the inability to

meet demand, the inability to meet quality requirements, or failed product in the

hands of the consumer. In any event, there are costs associated with failed

mechanisms, failure to meet demand, and failure to isolate nonconforming

products from the customer. Costs associated with immediate effects or other

effects in downstream processes within the manufacturing facility are

37

obtainable. Costs associated with effects downstream of the manufacturing

facility may be difficult to obtain. The columns titled “Immediate Failure Effects”

and “Downstream Failure Effects” in Table 4 (Part 1) and Table 4 (Part 2)

respectively will list potential failure effects for the process descriptions

associated with the band saw. Immediate effects are evident at the failed

processor. Downstream effects are evident at downstream processes or the

customer. Internal effects of nonconforming product propagating down stream

is increased rework or scrap during Incline Press assembly at a cost of $500

per incident.

3.10 Identifying Current Controls

Controls are sensors or procedures designed to detect and isolate

nonconforming product from propagating to downstream processes. For

existing processes, these items are usually listed on a control plan. These

items could be manual inspections, automated inspection systems, or go-no-go

gages. For sawed items, a long measuring gage can be used to measure

length.

The parts will be sawed in bundles of 10. The operator will check one

part of each bundle internal to the next cut. In addition, the band saw is

equipped with an out-of-square detector (OSD). The detector can stop the saw

cycle if the blade bows out-of-square a preset amount.

The band saw is equipped with a fault detection system. In most cases

when a failure occurs, the saw’s hydraulic motor will stop the sawing process

and display an error fault code. These error codes are listed under current

controls when applicable and are noted as “E-XXX.” Saw stoppage is a

process control that will preempt additional system failures or scrap production.

38

Saw stoppage is a prompt for the operator to review parts in process as

suspect nonconformance before releasing them to the next process.

3.11 Defining Occurrence, Severity, and Detection

Occurrence is the frequency of occurrence of the failure cause. For

reliability issues, occurrence is usually expressed as a Mean Time Between

Failures (MTBF) in hours. MTBF values may be provided by the manufacturer

based on reliability test or warranty data. Maintenance history of processors

may provide better MTBF estimates since the data is based on the processor in

its environment and utilization profile. Some component failures may not be

age-related. Therefore, a MTBF may not be attainable. Nautilus did not keep

historic maintenance information.

Severity of occurrence is the cost of the effect of the failure in terms of

damage or inability to isolate nonconforming parts. The severity results from

scrap, repair costs, lost throughput, inability to fulfill demand, quality reputation,

or harm to personnel.

Detection is the probability that the current controls can detect and

isolate nonconforming product from effecting downstream processes or

customers. Basically the detection probability is the assessment of a

company’s control plan. Historic information on scrap reports or return material

authorization from customers indicate the quantity of parts that get through

current controls.

3.12 Determining Cost of Failure

To determine and annualize the cost of failure, the analyst must have

the previous information developed in the PFMEA, scrap cost, cost of

39

downtime, cost for loss of opportunity, the cost of maintenance labor, the cost

of spare parts, and labor hours required to repair the failure. Maintenance

labor hours can be determined from historical data or through a Maintenance

Task Analysis (MTA). Mean corrective maintenance time (Mct) will be factored

with the maintenance labor wage to determine the corrective maintenance

labor cost. MDT may include administrative delay time or time to acquire parts

which are not in stock. Material costs are the costs of spares or consumables

which need to be replaced as a result of the failure. The cost of failure is the

sum of the following costs plus the material costs.

Scrap Cost = Pieces of Scrap * Scrap Cost

Cost of Idle Operator = MDT * Operator Wage

Cost of Lost Opportunity =

(MDT - Excess Capacity) * Hourly Cost of Lost Opportunity

Cost of Downstream Effects =

(1 - Scrap Detection %) * Pieces of Scrap * Cost of Downstream Effects

Corrective Maintenance Labor Cost = Mct * Maintenance Labor Wage

This section has described the application of the PFMEA to the Amada

band saw. Manufacturing system information has been used to determine the

cost of the failure. See Table 4 (Parts 1, 2, and 3) for the PFMEA. See Table

5 (Parts 1 and 2) for the annual corrective maintenance cost by component.

40

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43

Table 5. Band Saw Annual Maintenance Costs (Part 1).

MTBF |Scrap Scrap|MDT | Mct| Throughput|Scrap |Cost of Cost of Loss of

Corrective Maintenance (Hrs)|(Pcs) | Detection (%)|(Hrs) |(Hrs)| Loss (Hrs) Cost ($)|Operator |Opportun

Hydraulic Failure - 0.0 100% | 19.00) 4.00 §.6|$ - $ 285 | $ 1,718

Encoder Failure - 2.5 95%} 17.00) 2.00 3.6|$ 21|$ 255(|$ 1,104

Dull Blade 240 2.5 95%/| 0.33) 0.33 0.0|/$ 2148 5|$ -

Blade Slips - 0.0 100%| 0.33) 0.33 00;$ - $ §|$ -

Broken Blade - 2.5 100%| 0.33] 0.33 0.0/$ 21/$ 5|$ -

Speed Reducer Failure 61,200 0.0 100% | 19.00; 4.00 §.6|$ - $ 285 $ 1,718

Saw Blade Motor Failure - 0.0 100%| 17.00] 2.00 3.6|/$ - $ 255|$ 1,104

Cutting Fluid Pump Failure - 2.5 95% | 16.50} 1.50 3.1]/$ 21/$ 248|$ 951

Cutting Fluid Pump Clogged } 3,060 2.5 95%| 1.00| 1.00 0.0;/$ 21/$ 15 | $ :

Lack of Coolant Flow 120 2.5 95%| 0.25] 0.25 0.0/$ 21/$ 4|$ :

Cutting Fluid Filter Clogged 2,040 2.5 95%| 1.00] 0.50 0.0/$ 21/|$ 15 |$ -

Conveyor Motor Failure - 0.0 95%| 17.00/ 2.00 3.6|$ - $ 2551 $ 1,104

Brush Worn / Change 1,530 2.5 95%| 0.66; 0.66 0.0|/$ 21;$ 10|$ :

Brush Motor Failure - 2.5 95%| 15.50 0.50 2.1/$ 21/$ 2331 $ 644

| |

Table 5. Band Saw Annual Maintenance Costs (Part 2).

« Annual Cost

ost of Effects|of Failureto | Materlal| CMLabor| An « nual | Annuat Cost Per Task Torective Maintenance Downstream (Process Costs Costs | CM Cost of Failure; Cost of Failure

ailure $ - $ - $ 1,000 |$ 60 | $ - $ $ Encoder Failure $ 63 | $ - $ 2251 $ 30 | $ : $ - $ on ull Blade $ 631$ 2214 7 Blade Sips So es et Broken Blade $ - ($ -_ Ts 8818 TST S - ; 36 peed Reducer Failure $ - $ 196 - 5 Saw Blade Motor Failure | $ - Ts - : 750 ; 30 : ey oe 239

Cutting Fluid Pump Failure | $ 63 | $ - $ 250/$ 23 | $ - ; - ; 1 558 Cutting Fluid Pump Clogged | $ 631$ 193 |$ -|$ 151$ 29 1$ 293 : siz Lack of Coolant Flow $ 63 | $ 4,369 | $ -|1$ 4/§ 188 | $ 4,556 | $ ot Cutting Fluid Filter Clogged | $ 63/$ 2001$ Ts a(S 22(s : Conveyor Motor Failure $ - $ : $ 175 |$ 30 | $ - $ a 564 Brush Worn / Change $ 631$ 367 1/$ 151 10[$981$ wats a8 Brush Motor Failure $ 631 $ - $ 165 | $ 81$ - $ $ 1 135

Total | $ 9,564

4.0 _Reliability Centered Maintenance Analysis

4.1 introduction

Reliability Centered Maintenance Analysis is a systematic approach for

the development of an effective and documented preventive maintenance

program for an equipment or system. The RCM analysis consists of a

structured decision tree that defines effective and efficient preventive

maintenance tasks which will sustain the quality and throughput of a

manufacturing system based on maintenance and failure costs. Like the

FMEA, RCM is best used during the systems design phase. The RCM analysis

is also an effective tool for evaluating and improving existing preventive

maintenance programs.

The goals of RCM are to: (1) assess the less expensive maintenance

alternative, (2) establish the preventive maintenance schedule, (3) establish

preventive and corrective maintenance procedures, (4) establish resource

requirements, and (5) allocate maintenance task responsibility (operator,

electrician, mechanic, etc.). In general, the goal is to implement and maintain a

strategically scheduled/JIT preventive maintenance program and a responsive

corrective maintenance program which is effective and exhibits the lowest cost.

See Table 6.

In the process of developing the RCM program, extensive

documentation on the manufacturing system will be developed which will reveal

the companies current practices regarding operation, maintenance, product

quality, and safety. The structured review of the system will create the means

by which maintenance tasks are introduced and revised, failures modes,

causes, and effects are reported, and corrective maintenance actions are

defined. Maintenance actions can be recorded to provide a historical database

which can be used to improve the maintenance concept. RCM can also be

45

Table 6. Maintenance Cost Breakdown.

Cost Components Associated with Cost Components Associated with

Failure Preventive Maintenance

Labor Labor Materials Materials Diagnostic/Test Equipment Monitoring/Test Equipment Training Training Loss of Opportunity Contractual Delivery Loss of Customer Faith Scrap

Rework

Personnel Injury used to establish maintenance roles which are best performed by the machine

RCM can be

performed on all processes or on the critical processes as defined by a FMEA

operators, leading towards Total Productive Maintenance.

given limited resources.

To perform a Reliability Centered Maintenance analysis, the analyst

determines the modes by which a process will fail, failure frequency, the effects

of the failure, and the cause of the failure. The cost of the failure is calculated

based on corrective maintenance costs, scrap costs, rework costs, lost

opportunities cost, and the cost of defects reaching the customer. The analyst

also determines maintenance tasks which are technically feasible and effective

in preventing failure modes. The costs associated with the preventive

maintenance tasks must be defined. To determine the costs of each

maintenance alternative, the analyst must determine the maintenance task

procedures, material requirements, the personnel quantities and skill levels

required for performing the maintenance. Figure 11 shows the information

requirements needed for each step in the RCM analysis.

46

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47

The RCM analysis is best performed by an interdisciplinary group of

people with an operations, maintenance, or engineering background. The

analysts must be knowledgeable of the manufacturing system, the maintenance

concept, maintenance tasks and their effective application. The analyst's

knowledge and experiences form the major inputs to the RCM decision logic.

The RCM decision logic is flexible and should be customized to the

manufacturing and support capabilities of the manufacturing facility, if

applicable.

Four of the common RCM decision logics are: (1) MIL-STD-2173(AS) -

“Reliability-Centered Maintenance Requirements for Naval Aircraft, Weapons

Systems, and Support Equipment,"25 (2) AMC-P-750-2 - "Guide to Reliability-

Centered Maintenance,"24 (3) MSG-3, "Airline/Manufacturer Maintenance

Program Development Document,"25 and (4) Reliability-Centred Maintenance

\l.26 See Appendix A for a graphical representation of each decision logic.

Today, RCM is extensively applied within the airline industry where it

originated. Manufacturers are required to develop a maintenance program for

each new aircraft before it is introduced into service. The MSG-3 (or RCM)

analysis is an acceptable methodology for developing the maintenance

program. Presently, The United States Department of Defense uses RCM to

develop maintenance plans for systems and equipment. For these uses, RCM

was intended to optimize system reliability and insure mission success.

RCM has been used over a broad range of manufacturing industries

including railroad industries and automobile manufacturers. While mission

23 MIL-STD-2173(AS), Military Standard, "Reliability-Centered Maintenance Requirements For Naval Aircraft, Weapon Systems, And Support Equipment," AMSC No. N3769, U. S. Department Of Defense, Washington D.C., August, 1981.

24 AMC-P-750-2, U.S. Army Pamphlet, “Guide To Reliability Centered Maintenance," U.S. Department of Defense, Washington D.C.

25 MSG-3, Airline/Manufacturer Maintenance Program Development Document, Maintenance Steering Group 3 Task Force, Air Transport Association of America, March 1988.

26 Moubray, J., Reliability-Centered Maintenance - RCM-I|, Butterworth-Heinemann Ltd.,

Boston, Massachusetts, 1991.

48

success in most manufacturing applications is important, cost-efficiency of the

entire manufacturing system is paramount. John Moubray and associates have

assisted with the application of RCM at many industries including three power

generation plants, two railways, two automobile manufacturers, several food

manufacturing plants, two nuclear facilities, and mumerous_ other

manufacturers. The results of the RCM analysis as applied to an existing

manufacturing facility is a preventive and corrective maintenance plan which

will optimize system throughput and costs. See Figure 12.

Allison Gas Turbine Division of General Motors Corporation has

developed a computer program that automates the MSG-3 analysis logic.27

The program was designed to serve as a tool to present the decision logic to

the analyst and to document the analyst's responses. The analyst is

responsible for making decisions, not the software. The software prompts for

information and records it. This reduces the amount of work required to

perform the analysis as opposed to manually performing the analysis. It also

reduces the chance of error as a result of incorrectly following the decision

logic.

4.2 Maintenance Significant Items

Maintenance Significant Items are items whose failure: (1) could affect

safety, and/or (2) could be undetectable or are not likely to be detected during

operations, and/or (3) could have significant operational impact, and/or (4)

would have significant economic impact.28 They will be addressed through the

RCM analysis.

27 Callis, C.L. and F.E. David, "Automating the MSG-3 Analysis," Allison Gas Turbine Division, General Motors Corporation.

28 MSG-3, “Airline/Manufacturer Maintenance Program Development Document,” Maintenance Steering Group 3 Task Force, Air Transport Association of America, March 1988.

49

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4.3 Structurally Significant Items

Each structural item is assessed in terms of its significance to continuing

structural stability, susceptibility to any form of damage, and the degree of

difficulty involved in detecting such damage. Once this is established, a

maintenance program is determined which will assure continued structural

integrity by providing the means to demonstrate that catastrophic failures due

to fatigue, corrosion, or accidental damage will be avoided throughout the

operational life of the structure.29

The work group must analyze the structurally significant items using two

analyses: Fatigue Damage Analysis and Accidental Damage/Environmental

Deterioration (AD/ED) Analysis. Fatigue analysis separates SSI into either

damage tolerant items or safe-life items. Items classified as damage tolerant

are routinely inspected for noticeable failure or redesigned. An example of an

SSI would be a mezzanine support or pallet rack. Accidental damage could

occur if a negligent tow motor driver collided and bent the support structure.

Fatigue from cyclic loading or corrosion could also lead to decreased structural

integrity.

AD/ED Analysis requires the analyst to determine inspection techniques

which will detect anticipated accidental damage or environmental damage.

These inspection techniques dictate where to look and what signs reveal

damage. Inspection requirements for timely detection of AD/ED must then be

determined.

Decision logic for SSI analysis is graphically represented in Figure 22 in

Appendix A. This project will not address SSIs. SSis would not be made

evident through a PFMEA.

29 MSG-3, Airline/Manufacturer Maintenance Program Development Document.”

51

4.4 RCM Decision Logic

The RCM decision diagram will pose a series of questions which will

prompt the analyst to define a maintenance plan using the information obtained

from the FMEA. The analyst will review the indicators and consequences of

failure then determine the maintenance tasks which will cost-effectively prevent

or correct the failure. Each question of the RCM decision logic will help the

analyst decide which maintenance option is less expensive, corrective or

preventive maintenance. In the decision process, the analyst must determine

which, if any, preventive maintenance actions will significantly increase process

reliability. The analyst will also establish alternative preventive maintenance

procedures, frequencies, resources requirements, and the cost associated with

each alternative.

In general, RCM decision logic first classifies failure modes by the ability

to detect them. An operator must first be able to detect the failure mode or the

effects of the failure mode before multiple failures are allowed to occur. This

consideration will guide the analyst in determining what information the

processors or work-in-process will provide in assessing the necessity and

timeliness of maintenance requirements. This information was defined in the

PFMEA current controls list.

Hidden failures are failures with no direct effects or consequences to the

operating system. Hidden failures may allow multiple failures to occur which

can impact the system catastrophically. Consider the generator in a car as an

example. A generator can fail and not be detected by the operator till the

battery fails. The system is not impacted till the battery's energy is completely

consumed. If the failure is hidden, the RCM decision logic suggests a series of

preventive maintenance tasks which may make the failure visible. Inspection

or built-in-testing are the most common form of identifying hidden failures. If a

52

preventive maintenance task is not feasible or cost-effective for unmasking the

hidden failure, a design change may be warranted if the failure consequences

are severe. Otherwise, corrective maintenance of the multiple failures is the

preferred maintenance action.

The next step in the RCM decision logic is to classify failures according

to their severity. Severity may be defined in terms of safety, quality, reputation,

lost production time, cost, or a combination thereof. In general, failures are

placed in one of four categories: Hidden, Safety/Environment, Operational,

and Non-operational. Failures which result in personnel injury or

environmental damage clearly belong to the Safety/Environment category.

Only the RCM Il logic includes environmental concerns. Although the severity

of these damages may be negligible to system operation, the company's

responsibility to personnel and the environment are unmeasurable. These

failures must be avoided at all costs since these resources are invaluable.

Determining cost-effectiveness in this category is very difficult. |The

documentation and task choices when reviewing these failure modes can

determine the extent to which the company has committed to preventing these

failures and can possibly be used as a means to declare the extent of

negligence and/or liability the company must burden, if any, in the case of a

safety/environmental failure.

Operational failures impede or halt production, which results in a

corrective maintenance cost, downtime production loss, and possibly a loss of

customer faith. These three costs can be used to cost-justify a preventive

maintenance task aimed at reliably preempting the failure.

Non-operational failures do not affect system throughput. Although non-

operational failures do not present a loss of production, management policies

may assign a value to some non-operational failures. For example, a bent car

fender would be a non-operational failure, since the fender does not affect

53

vehicle operation. Suppose a chauffeur agency had a vehicle with a bent

fender. The bent fender may degrade the clientele's perception of the

company, therefore warranting repair. Associated with each category of failure

modes is a flow diagram of questions which are designed to determine the

most effective course of maintenance.

Some preventive maintenance tasks will be determined prior to the use

of the maintenance task decision logic. In the case of a purchased system, the

manufacturer may have recommended some maintenance tasks. Total-loss

lubrication points will be listed and scheduled without analysis. The cost of

analysis of total-loss points often outweighs the cost of maintenance.

Next, the maintenance task decision logic associated with each failure

category is used to suggest maintenance tasks in order to preempt the failure.

These maintenance task categories are on-condition, scheduled restoration,

and scheduled discard. The analyst must consider if a task is technically

feasible and if the task will prolong or restore the component back to its original

reliability. The task cost will be used to answer the question of whether the

task is economically feasible as opposed to the default action. One must

ultimately consider the life-cycle cost of the failure and its impacts to the

system, personnel, and the environment. In the event that preventive

maintenance costs more than failure costs, the default action “no scheduled

maintenance” is preferred, except under the safety/environmental category.

Failures which harm personnel or the environment will require compulsory

redesign.

4.5 RCMIl Analysis Example

The RCM analysis performed in this project will utilize the RCM Il

decision logic. The RCM II decision logic is preferred instead of the other three

54

because it has been applied previously in private industry and because it

addresses environmental concerns.

The RCM II will begin with a series of questions which as a result will

classify the failure into one of the following categories: Hidden Failure,

Safety/Environmental Failure, Operational Failure, and Nonoperational Failure.

After the classification, each failure mode must proceed through the

maintenance planning decision logic associated with the classification.

The only discernible difference between the task logics is the default

action. The default action is the action the organization should take if the

failure is not technically or economically feasible to prevent. Given a hidden

failure, if multiple failures do not effect personnel safety or the environment,

there is no scheduled maintenance. Redesign is voluntary if feasible. If

personnel safety or the environment is in jeopardy as a result of a hidden

failure, the system should be _ redesigned. The default action for

safety/environmental failures is compulsory redesign. The default actions for

both operation and non-operational failure is no scheduled maintenance,

redesign if feasible. Table 7 summarizes consequences and default actions.

Table 7. Default Actions.

Consequence Default Action Hidden, Safety/environmental Compulsory Redesign Hidden, Non-safety/environmental No scheduled maintenance.

Redesign if feasible.

Safety/Environmental Compulsory Redesign Operational No scheduled maintenance.

Redesign if feasible.

Non-operational No scheduled maintenance. Redesign if feasible.

The analyst will first categorize the failure of the band saw into a

consequence category by proceeding through the decision logic in Figure 13.

55

Will the loss of function

caused by this failure mode on its own become evident to the operating crew under

normal circumstances? Yes

Does the failure mode

cause a loss of function Yes

or other damage which could hurt or kill someone?

No \

Hidden Failure

No

Does the failure mode cause a

loss of function or other

damage which could breach any known

environmental standard or

reguiation?

Yes

No

Does the failure mode have a direct adverse effect on

operational capability (output, quality, customer service or operating costs in addition to

the direct cost of repair?

Safety/Environmenta

Yes

No

Nonoperational

Operational

Figure 13. Classification Decision Logic for RCM II.%°

30 Moubray, John. Reliability-centered Maintenance - RCM II.

56

The results of the consequence analysis is in Table 10 under the column

“Consequence.” With the exception of the brush, all consequences are

operational. The brush consequences are hidden. However, the brushes

hidden consequences will not effect personnel safety or the environment.

Therefore, all default tasks in this example will be “no scheduled maintenance.”

Please note that failure causes involving hydraulic pressure settings and

scrap interference are not being pursued through the RCM analysis. Pressure

settings are made by the operator based on material configuration. High

pressure settings on the clamps will distort tubing while in the vise. These

parameters will be established in the process instructions for the operators. It

will be assumed that these settings are correct, thus not a maintenance issue.

Scrap interference is an uncommon incident where scrap slugs fall

behind the rear vice and the back stop. The scrap slug interferes with the rear

vice reaching the back stop and limit switch. Therefore the machine does not

cycle. This condition is recognized and fixed by the operator.

4.6 Manufacturer’s Recommended Maintenance Tasks

Since the Amada band saw was manufactured by an original equipment

manufacturer (OEM), the manufacturer has probably suggested certain

preventive maintenance tasks aimed at extending processor life and preventing

some failure modes. Additionally, the Operator's Manual will provide some

maintenance instructions and trouble shooting tips. Table 8 represents the

preventive maintenance tasks suggested by Amada. These items are listed in

the maintenance plan. They are denoted by “(MR)” for “manufacturer

recommended.”

57

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4.7 Total-loss Lubrication Points

The analyst should list all total-loss lubrication points. Total-loss

lubrication points such as grease nipples, slides, lead-screws, and open

lubrication systems should not be analyzed as part of the RCM analysis

because maintenance costs are relatively inexpensive. Whereas analyzing

total-loss lubrication for proper maintenance intervals and costs may be

unnecessarily expensive. %2

Since these items are typically open, replacement of lubrication is

frequent. Lubrication in open systems is easily contaminated and _ lost.

Fortunately, all total-loss lubrication points on the Amada are listed in the

operator's manual and are part of the manufacturer-recommended preventive

maintenance plan. These tasks are best allocated to the operator and defined

in the process instructions.

Closed lubrication systems such as gearboxes or engines are

determined during the task decision process. These lubrication points usually

require checking fluid levels, changing fluids, and/or analyzing the condition of

the fluid.

4.8 Maintenance Task Decision Logic

Next, the analyst must proceed through the maintenance task decision

logic. The maintenance task logic is represented in Figures 14, 15, 16, and 17.

The following sections will discuss the task options in detail.

32 Moubray, John. Reliability-centered Maintenance - RCM II.

59

Will the loss of function caused by this failure mode on its own become evident to the operating crew under

normal circumstances?

No

Is a task to detect whether the failure is Yes occurring or about to

occur technicallyfeasibie and worth doing?

Scheduled

On-conditionTask

qT

Nol

Is a scheduled

restoration

task to reduce the failure

rate technically feasible and worth doing?

Scheduled

Restoration Task

No

Is a schedule discard

task

to reduce the failure rate creed’

technically feasible and worth doing?

No

\

Is a failure-finding task to detect the failure

technically feasible and worth doing?

Scheduled Failure-finding Task

No

Could multiple failure | Yes affect safety or environment?

Redesign is Compulsory

No,

| No Scheduled

Maintenance -

Redesign if Cost Effective

Figure 14. Maintenance Task Decision Logic for Hidden Failures.**

33 Moubray, John. Reliability-centered Maintenance - RCM II.

Does the failure mode

cause a loss of function | No or other damage which

could hurt or kill

someone?

Yes

Is a task to detect whether the failure is occurring or about to

occur technically feasible and worth doing?

Is a scheduled restoration

task to avoid the failure rate technically feasible

and worth doing? —__1

fo No

Is a schedule discard

task

to avoid the failure rate technically feasible and worth doing?

Does the failure mode cause a

loss of function or other

damage which could breach any known

environmental standard or regulation?

a Yes

Scheduled

On-conditionTask

Yes —

Scheduled

Restoration Task

Yes

a

No

ls a combination of task

to avoid failures

technically feasible and worth

doing?

Scheduled

Discard Task

Yes

Combination of

Tasks

No

Redesign is Compulsory

Figure 15. Maintenance Task Decision Logic for Safety/Environmental

Failures.34

34 Moubray, John. Reliability-centered Maintenance - RCM II.

Does the failure mode have a

direct adverse effect on operational Capability (output, quality, customer

service or operating costs in addition to the direct cost of repair?

|

Yes

is a task to detect

whether the failure is Yes Scheduled

occurring or about to i On-conditionTask occur technically feasible

and worth doing?

Is a scheduled restoration

task to reduce the failure rate technically feasible | Yes

and worth doing? |

——

ls a schedule discard task Yes

to reduce the failure rate technically feasible and worth doing?

Scheduled

Restoration Task

No

Scheduled

Discard Task

No Scheduled

Maintenance -

Redesign if Cost Effective

Figure 16. Maintenance Task Decision Logic for Operational Failures.5

35 Moubray, John. Reliability-centered Maintenance - RCM Ii.

Does the failure mode have a

direct adverse effect on operational capability (output, quality, customer

service or operating costs in addition

to the direct cost of repair?

No

Is a task to detect whether the failure is Yes occurring or about to

occur technically feasible and worth doing?

yn

Is a scheduled restoration

task to reduce the failure >

rate technically feasible Yes and worth doing?

Scheduled

On-conditionTask

Scheduled

Restoration Task

No

Is a schedule discard

task Yes

to reduce the failure rate

technically feasible

and worth doing?

Scheduled

Discard Task

No

| No Scheduled

Maintenance -

Redesign if Cost Effective

Figure 17. Maintenance Task Decision Logic for Nonoperational Failures.

36 Moubray, John. Reliability-centered Maintenance - RCM II.

63

4.9 On-condition Tasks

On-condition tasks involve monitoring a system or component that tends

to fail over a period of time (P-F interval). On-condition tasks are system

inspections which are used to look for potential failures. On-condition tasks

can involve inspection through human senses, monitoring of process feedback,

inspection of product quality, and condition monitoring. The inspection may

reveal a needed preventive maintenance action or estimated time to failure. To

assess a processor condition, an attribute must be measured and compared to

a control signature. The control signature(s) of the attribute are used to assess

the condition of the machinery given a condition measurement. For example, a

spectrometer analysis of a degreaser sample may provide a parts per million

(PPM) count of suspended grease. This PPM measurement would then be

compared to a control signature. In this case, the contro! signature would likely

be an upper limit grease PPM count, which when exceeded, indicates the need

to drain, centrifuge, and replace the degreaser. In the event that the PPM

count was below the upper control limit, personnel may compare the

measurement to historical data, providing an estimate of the life of the

degreaser.

Typical processor instrumentation which may indicate imminent and

approaching failure are temperature or pressure gauges. Monitoring also

involves noticing unusual physical attributes such as odor, noise, or vibration to

predict failure. These symptoms usually indicate to the operator that failure is

approaching. Predictive monitoring is a form of on-condition monitoring, where

machine conditions are tracked and assessed using a cycle counter or a time

clock.

For an on-condition task to be effective, a component condition that

exhibits potential failure (P) must be detectable and task frequency must be

64

smaller than the component's P-F interval. Based on the P-F interval, on-

condition tasks may allow maintenance to schedule Just-In-Time restoration or

discard tasks at the processor’s next convenience. This would also avoid some

or all of the cost of system down time. If the P-F interval is too short or

inconsistent, on-condition tasks are not feasible. A short P-F interval may not

afford maintenance the opportunity to perform the maintenance task when the

processor is available.

On-condition tasks have many benefits. In the event an on-condition

task can detect potential failure with age-related items, the component can be

used over its entire useful life. Whereas, scheduled tasks may recondition the

system and incur the associated cost well before actual failure of the

component. Using all of the components useful life before maintenance may

save a manufacturing organization considerable money.

On-condition tasks due require time and money. It must be technically

feasible to monitor the system. The on-condition task must clearly define a

potential failure. Developing experience or history on performance baseline

and thresholds will assist the analyst in clearly defining a potential failure

mode.

If a feasible on-condition task cannot be determined, scheduled

restoration or discard tasks can be considered for items that exhibit age-related

failure. The analyst must resort to default tasks for items that do not exhibit

age-related failure.

4.10 Scheduled Restoration Task

Scheduled restoration is the act of refurbishing a component to its

original resistance to failure at a predetermined interval. To consider a

scheduled restoration task, the component must have a useful life. If failure is

65

not age-related, then the restoration task does not preempt a failure due to

wear. In fact, unnecessary restoration may induce failures. The frequency of a

scheduled restoration task is based on the components useful life.

Typical restoration tasks are cleaning, fluid replenishments, or painting.

An example of a restoration task would be turning brake rotors to restore a

uniform surface for the brake pads.

Scheduled restoration tasks have benefits over corrective maintenance.

Restoration does not necessarily incur as much material costs as replacing the

component. Restoration would prevent costs of secondary damage that may

be caused by component failure. Restoration must be significantly less

expensive than discarding, else discarding would be preferred. The largest

benefit to any scheduled task is, to a certain degree, it can be done at the

processor’s convenience.

Teamwork between maintenance and the scheduling function could

reduce or eliminate the cost associated with down time. Administrative delays

and procurement lead times would be external to the machine down time. On

the downside, scheduled restoration will typically require additional labor and

down time to restore the item.

4.11 Scheduled Discard Task

A scheduled discard task is the scheduled restoration of the system to a

reliable condition by replacing a component which is near failure. A scheduled

discard task is very similar to a scheduled restoration task. The discard item

must have a definable useful life. A discard task is preferred over a restoration

task if it is not technically feasible to restore the component or if it is less

expensive to discard the component. The discard task interval is based on the

useful life of the component.

66

The scheduled discard task can also be done at the convenience of the

processor. The costs associated with discard tasks are comparable to those of

corrective maintenance. The only exception is that the scheduled task may

avoid costs associated with down time.

Since preventive rework and discard task frequency are determined by a

predetermined MTBF, rework/discard tasks are performed based on the cycle

clicks, hours of utilization, or calendar intervals. Condition monitoring can be

used to establish maintenance click/clock intervals or calendar intervals.

4.12 No Scheduled Maintenance (Corrective Maintenance)

In the event corrective maintenance is the preferred option, a responsive

corrective maintenance plan should be defined. A responsive corrective

maintenance plan entails equipment, indicators, and procedures for diagnosis,

disassembly, rework/replace, repair verification, data collection, and sparing.

When performing the RCM, corrective maintenance protocol (i.e. lockouts and

diagnosis) and maintenance instructions for processors will be developed.

During a corrective maintenance action, information should be collected which

would be used to develop, reaffirm, or revise maintenance standards and

policies. This information includes machine downtime, time to repair,

counter/timer readings, cause of failure, material cost, and scrap cost.

Direct costs associated with corrective maintenance include labor, parts,

diagnostic equipment, process scrap/quality rejects, contractual deadline costs,

and the lost opportunity cost of production (if it decreases bottleneck

throughput).

4.13 Compulsory Redesign

The default action for safety and environmental failures is compulsory

redesign. Redesign could entail incorporating built-in test equipment, condition

monitoring sensors, or building redundancy into the system.

4.14 Selecting the Maintenance Task

At this point, the analyst must proceed through the maintenance task

logic for each failure mode. Feasible preventive maintenance tasks are

determined by the analyst and their cost is estimated. Table 9 lists feasible

preventive maintenance tasks for age-related components and their cost

estimates.

Task PM Cost = (Material Cost + Labor Cost + Overhead Cost)

Annual PM Task Cost = Task Frequency * Task PM Cost

For on-condition PM tasks, the cost of discarding the item upon potential failure

is the same as the cost of corrective maintenance. Therefore, the cost of

corrective maintenance is used as the cost of the on-condition discard task.

This assumes that the estimated MTBF is the life of the component. Only

historical data will help define a more accurate MTBF.

When choosing which task to perform, compare the annual costs of the

proposed PM tasks versus the annual cost of failure. Consider the

manufacturing facility's maintenance philosophy in this decision. In the case of

operational failure, this analyst believes that PM tasks should be chosen over

CM tasks if the costs are comparable. Since the CM task estimations are

68

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based on MTBF estimations, and on-condition tasks are feasible on most age-

related components, this analyst is willing to risk a $500 error that PM is

significantly less expensive then CM. Since this analyst is biased towards PM,

a $500 factor will be included in the task decision.

If Annual CM Cost + $500 < Annual PM Cost, perform CM, else perform PM.

When historical maintenance data defines better variable estimates, a factor

may not be desired.

If there are alternative PM selections with comparable costs, on-

condition tasks are preferred to scheduled restoration/discard tasks. This too

is a decision based on the manufacturing facility’s maintenance philosophy.

Again, this analyst prefers using components to potential failure until a reliable

and consistent life can be determined.

Maintenance items that have zero MTBF are items whose failure is not

age-related. For these items, scheduled restoration or discard is not an option.

Therefore, if condition monitoring tasks cannot be determined, “no scheduled

maintenance” is the default task.

The resulting maintenance decision based on the maintenance task

decision logic is listed under “Proposed Task” in Table 10. In the table, each

question in the maintenance task logic is answered, forming the documented

maintenance plan. Table 11 provides the cost for each PM task.

4.15 Walk-throughs

After the maintenance tasks are selected, the analyst may want to

consider scheduling walk-throughs as a maintenance task. A walk-through is

basically a walk through the plant inspecting items for accidental damage or

70

structural damage. For example, aisle traffic around the saw may have

damaged a hydraulic hose. An alternative to a walk-through is having

operators perform an overall visual inspection of their area. With proper

housekeeping, the operator should be able to spot accidental damage or leaks

during everyday use of the equipment. This author believes daily

housekeeping is essential and those activities are directed by process

instructions.

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16

5.0 Maintenance Plan Summary

The estimated annual cost for the proposed maintenance plan as

described in Table 12 is $2,293. See Table 11 for a preventive maintenance

task summary. This methodology provides an initial maintenance plan. As

maintenance and failure data emerge from the manufacturing system (failure

rates, failure costs, preventive maintenance effectiveness, etc.), the

maintenance plan should be reviewed, evaluated, and revised as necessary

using the FMEA and RCM to ensure the most cost-effective, efficient

maintenance plan.

6.0 Conclusions and Recommendations

This project has demonstrated that the PFMEA and RCM analysis can

be used to define a maintenance plan for manufacturing processors within a

manufacturing system. The PFMEA assists the analyst in determining failure

causes. The impact of these failures can be qualified as a cost of failure with

the availability of certain system information. The RCM analysis will logically

direct the analyst towards viable maintenance tasks. The expertise of the

analyst must determine if tasks are technically feasible and effective since

those answers are situation-dependent. As the cost of alternative PM tasks are

compared to corrective maintenance tasks, a maintenance decision based on

cost can be made.

This methodology would be useful in the design phase to assess the life-

cycle cost of a system design. This methodology can be used to estimate the

cost of maintenance. The life-cycle cost of the system can then be estimated

from estimates of research and development, construction, start-up, operation

77

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78

and maintenance, and system disposal estimates. Given multiple alternatives,

a decision on the preferred system can be made based on life-cycle costs.

After each iteration of the methodology, data should be collected from

the system to reaffirm or revise the maintenance decision. Data collected from

the manufacturing system may provide move accurate estimates allowing the

analyst to reiterate the procedures and improve the plan.

Further study should be performed concerning down time associated

with function-related failure. The author's experience is that down time related

to function-related failure is greater than down time related to equipment

failure. Although these failure modes may show up on the PFMEA, they are

not issues that will appear in the maintenance plan. They are process control

issues under the control of the operator. There may be a decision logic or

procedure that will assist in establishing comprehensive process instructions,

work instructions, and reaction plans for these issues from the PFMEA.

79

Appendix A - RCM Decision Logic Diagrams

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structural itams | !

Is item No | structurally Other Structure

significant?

Yes |

__f . Accidental i t & Categorize &

Catege SSI AD/ED Analysis Damage and list as Other ; Environmental | gs

Anaiyze for FD ; ' tructure and ADIED Detenoration Analysis

FD Analysis | | | —__f ; | ts other structure |

i { similar to existing | Evsuate t , Is SSI damage ins pection j secre? | ' tolerant? fequirements for mt

| detecting AD/ED Yes Yes | No for al SSIs

| y aR

+ fp Dam : . Tolonmnt Safe-Life | Accidental | Environmental |

' Damage | Deterioration | | po : ____t__, ! 1 id | SwG

. Categorize & Est recommends | Categorize & | as SL: Mfr Inspection . and/or selects | listasDT | determines irements i maintenance |

safe-tfe Emits and require iL includes with SSI | for timety

poaab ean | ADIED forall | | airworthiness or al Is FD detection | No imitations | SSis | dependent on | L_ J a | scheduled inspections? | | \ |

{ i

Yes t ; —_——. Preliminary | |

| Adequate residual ! : ! . | strength with | ' Maintenance ec

| extensive damage | : Pian | thatls readily | ' ‘ ee nea \ detectable during ; :

| routine aircraft | ! operation; or = | | ;

| damageis | | | | indicated bya | | \ | safe malfunction | : | Overiay task

| | fromeach | _——___t___ ‘| damage |

Is scheduled N | No scheduled . i : evaluation & | fatigue related | NO a fatigue related i consolidate: | inspection inspection submit to ISC | required? required | fro approval |

Yes "and inclusion | ! , | in MRB report ;

Can FD be | Can FD by | Proposal detected by visual No detected by NDI | i

inspection at fhods at practical | practical | intervals? intervals? 7

Ave fatigue Improved access inspection No and/or redesign requirements §(_—-——————™ may be read, or

feasible according classify es to SWG? safe-ife?

Yes Fo

Figure 22. Structural Significant Item Decision Logic.*'

41 MSG-3, Airline/Manufacturer Maintenance Program Development Document.

Appendix B - Maintenance Task Analysis

A Maintenance Task Analysis will provide a structured method of

determining maintenance requirements associated with a failure mode or

preventive task. Maintenance Task Analysis will also provide the analyst with

the information necessary to determine task productivity.

The first step in defining maintenance tasks is defining the maintenance

requirement. The maintenance requirements result from the failure modes as

defined by the PFMEA. They also result as a formulation of tasks aimed at

preempting the failure modes defined by the PFMEA. After defining the

maintenance requirement, the analyst must define the tasks which will correct

or prevent the failure. This information can usually be found in the

manufacturer's documents or developed by experienced maintenance

professionals. For each task, the analyst must determine the elapsed time

needed to perform the task, tool and equipment needs, the necessary

personnel skill level, and replacement parts associated with the task. 42 This

information, along with the MTBF, will allow costing of the maintenance

requirement. Figure 23 diagrams information sources and information flow

through the MTA. Tables 11 and 12 represent a MTA on changing the

hydraulic fluid associated with the Amada HFA-330 band saw.

42 Blanchard, B.S., Logistics Engineering and Management, Prentice Hall, Englewood Cliffs, New Jersey, 1992.

86

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Appendix C - References and Additional Reading

AMC-P-750-2, U.S. Army Pamphlet, “Guide To Reliability Centered Maintenance,” U.S. Department of Defense, Washington D.C.

Author Not Listed, "Computerizing Maintenance Information,” Plant

Engineering, 1991 Encyclopedia, July 1991, pp. 218-219.

Amada, “Horizontal Bandsaw HA-330/HFA-330 Operator's Manual.”

Blanchard, B. S., Logistics Engineering and Management, 4th. Edition,

Prentice-Hall, Englewood Cliffs, N. J., 1992.

Blanchard, B.S. and W.J. Fabrycky, Systems Engineering and Analysis, Prentice Hall, Inc., Englewood Cliffs, New Jersey, 1990.

Blanchard, B.S., Verma, D. and Elmer L. Peterson, Maintainability: A Key to

Effective Serviceability and Maintenance Management, John Wiley & Sons, Inc. New York, New York, 1995.

Blanchard, B.S., Brennan Bowen, and Dinesh Verma. "A Review of Reliability Centered Maintenance (RCM) Approaches." Systems Engineering Design Laboratory, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061-0118, 1993.

Borgovini, R., Pemberton, S., and D. Russell. “Failure Mode, Effects, and Criticality Analysis (FMECA),” Reliability Analysis Center, Rome, NY operated by IIT Research Institute, 1992.

Bowen, Brennan and Dinesh Verma, "Manufacturing Process Improvement

Through the Application of the Failure Mode, Effects, and Criticality Analysis." Proceedings of the Fourth FAIM Conference, Blacksburg, Virginia, Spring 1994.

Bowles, John B., and Colon E. Pelaez, “A Comparison of Commercial FMEA/FMECA Programs," University of South Carolina, Columbia, S.C. 29208, 1991.

Callis, C.L. and F.E. David, "Automating the MSG-3 Analysis," Allison Gas Turbine Division, General Motors Corporation.

90

CARA FMECA (Software). Technica International, Suite 800, 1440 N. Harbor Blvd., Fullerton, CA 92635. (714) 447-9400.

Chrysler Corporation, Ford Motor Company, General Motors Corporation,

Reference Manual, Potential Failure Mode and Effects Analysis (FMEA), Second Edition, February 1995.

Cooper, Chris, "Desert Island Data,” Manufacturing Engineering, October 1992,

pp. 36-37.

Criswell, John W., Planned Maintenance for Productivity & Energy

Consumption. The Fairmont Press, Inc., Atlanta, GA, 1983.

Enelow, Micheal, "Go With the Flow," Manufacturing Engineering, February 1992, pp. 11-12.

Ertas, Atila and Jesse C. Jones. The Engineering Design Process. John Wiley & Sons, Inc., New York, 1993.

FMEAPlus (Software). Non-Ford Version: Adistra Corporation, 100 Union Street, Plymouth, MI 48170. Ford Version: Ford Motor Company, 1994.

FailMode (Software). Item Software Limited, Fareham, Hampshire, England, PO15 5SU.

Failure Modes & Effects Program (FME) 1.0 (Software). Powertronic Systems,

Inc., P.O. Box 29109, New Orleans, LA 70189. (504) 254-0383.

Ginzel, E. Charles and Dinesh Verma, "FMECA: Recommendations for

Improved Application." Technical_ Proceedings - The 28th Annual International Logistics Symposium, August 1993.

Goldratt, Eliyahu and Jeff Cox. The Goal: A Process of Ongoing Improvement,

Second Edition, North River Press, Croton-on-Hudson, NY, 1992.

Hamrick, James. "Eastward With TPM and CMMS," Industrial Engineering,

October 1994.

Hannan, Vince and Daniel M. Keyport, "Automating a Maintenance Work Control System,” Plant_Engineering, Vol. 45, No.2, December 1991, pp. 122-124.

91

Koelsch, James R., "A Dose of TPM: Downtime needn't be a better pill,”

Manufacturing Engineering, Vol. 110, No. 4, April 1993, pp. 63-66.

Kurz, Eberhard and Dieter Eden, "CIM-Maintenance - Information and

Document Management for the Maintenance of Aircraft," International Journal _of Flexible Automation and Integrated Manufacturing, Volume 1 Issue 1, 1993. CRC Press, Ann Arbor, pp. 1-10.

MIL-STD-1629A, “Procedures for Performing a Failure Mode, Effects, and Criticality Analysis’, Department of Defense, Washington, D.C.

MIL-STD-2173(AS), Military Standard, "Reliability-Centered Maintenance Requirements For Naval Aircraft, Weapon Systems, And Support Equipment," AMSC No. N3769, U. S. Department Of Defense, Washington D.C., August, 1981.

MSG-3, “Airline/Manufacturer Maintenance Program Development Document,” Maintenance Steering Group 3 Task Force, Air Transport Association of America, March 1988.

Maquire, Michael, "Predictive Maintenance: What does it do?,” Electrical World, Vol. 206, No.6, June 1992, pp. 11-12.

Mobley, R. K., Introduction to Predictive Maintenance, Van Nostrand Reinhold, New York, 1990.

Moubray, J., Reliability-Centered Maintenance - RCM-il, Butterworth- Heinemann Ltd., Boston, Massachusetts, 1991.

Nakajima, Seiichi. Introduction to Total Productive Maintenance, Productivity Press, Cambridge MA, 1988.

PC-FMECA Version 2.7 (Software). Management Sciences, Inc., 6022 Constitution N.E., Albuquerque, NM 87110. (505) 255-8611.

Patton, Joseph D. Jr. Maintainability and Maintenance Management,

Kingsport Press, 1980.

Reich, Hans, Maintenance Minimization for Competitive Advantage: A Life

Cycle Approach for Product Manufacturers and End Users, Gordon and

Breach Science Publishers, Langhorne, Pennsylvania, 1994.

92

Relex FMECA (Software). Innovative Software Designs, Inc. One Kimball Ridge Court, Baltimore, MD 21228. (301) 747-8543.

Smith, A.M., R.V. Vasudevan, T.D. Matteson, J.P. Gaertner, "Enhancing Plant

Preventive Maintenance Via RCM", 1986 Proceedings of the Annual Reliability and Maintainability Symposium.

Titan Software Corporation, "Maintenance: Profit Center 2000," Plant

Engineering, March 1992, pp. 101-112.

Titan Software Corporation, "Plant Maintenance As Profit Center: Rethinking Our Priorities," Plant Engineering, 1991 Encyclopedia, July 1991, pp. 228- 230.

Titan Software Corporation, "How to Select and Get the Most From a CMMS,"

Plant Engineering, 1991 Encyclopedia, July 1991, pp. 233-235.

Verma, D., "A Causal Emphasis during the Failure Mode, Effects, and Criticality Analysis", Invited Paper, International Logistics Conference, University of Exeter, Exeter, England, June 1993.

Verma, D. and B. Bowen, Process FMEA Training Manual, Federal Mogul Corporation, Blacksburg, Virginia 24060. December 1992.

Verma, D., B. Bowen, B.S. Blanchard, and L.B. Weddle, “Utilization of the

FMEA to Improve Manufacturing Process Efficiency: A Commercial Case Study,” Technical Proceedings - The 28th _ International Logistics Symposium, August 1993.

Wireman, T., Inspection and Training for TPM, Industrial Press, Inc., New York,

1992.

Wireman, T., Total Productive Maintenance: An American Approach, Industrial

Press, Inc., New York, 1991.

Wireman, T., World Class Maintenance Management, Industrial Press, Inc.,

New York, 1990.

93