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ISPEKnowledge Brief

by Mel Bahr

Fundamental

KB-0023-Oct11

Using OEE for Packaging Line Improvement

IntroductionThere is a great deal of interest in Overall Equipment Effectiveness (OEE). The entry for OEE in Wikipedia is: “OEE is a hierarchy of metrics which evaluates and indicates how effectively a manufacturing operation is utilized. The results are stated in a generic form which allows comparison between manufacturing units in differing industries. It is not however an absolute measure and is best used to identify scope for process performance improvement, and how to get the improvement.” This definition best describes the objective of this Knowledge Brief, which is to understand the metrics used, the basics of conducting an OEE study, and how to implement OEE improvement.

OEE is a tool that can be used to analyze the overall utilization and operation of a line. It includes all of the activities associated with a line’s operation such as clearing, cleaning, lot change, and the effectiveness of all equipment during runtime. For the purposes of this document, comments will be directed to those

operations associated with a primary or secondary packaging line located in a pharmaceutical area.

The tasks associated with an OEE study are to identify problems and issues, measure their severity, and improve productivity. The data that is generated by an OEE study are useful topics for a Lean Event (solving the problems) or a Sustainability initiative.

This Knowledge Brief is not intended to promote a single method or means of conducting an OEE study, nor is it intended to promote any company or organization. Instead it looks briefly at industry wide, commonly accepted methods applied in a practical manner.

Gathering, Calculating, and Using the DataThere are many software options for assisting in gathering and calculating the data from a production line. As of this writing, Google had 198,000 software listings, 60,000 of them are promoted as free. There are web based systems available to collect data online as well as Consulting Engineering firms that will

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come to your site. More commonly are internal networks (SCADA) that collect real time or end of batch data generated by the equipment on the line.

An entry level OEE study is best done using a spreadsheet. Setting up the spreadsheet will help with the understanding of the metrics of what and how data is best measured in your situation. After use (processes confirmed), the metrics can be transposed into a larger complex system. Reminder: It should be recognized that the spreadsheet approach will deliver information, but there may not be the level of detail that more complex systems can provide. Operators who are also compiling the spreadsheet information may not record all the downtime - they may consider a routine adjustment as “normal,” for example. For many situations, this level of detail is all that is necessary to identify opportunities for improvement, and it is a low cost approach.

Start with an UnderstandingDetermining “what” should be measured is a key step in an OEE study.

1. Set the boundaries. What is to be included? People, Process, Materials and/or Equipment? Which of these can be changed or not changed due to constraints, real or imaginary?

2. Set the magnitude of the study. Applying OEE to an evaluation of a single piece of equipment (versus a line) may change your definitions of Availability, Performance, and Quality. There may be immediate issues to be dealt with that limit the scope and size of the study.

3. Define the role of using OEE for the purchasing and acceptance of new or used equipment.

The Formula and the Basics:Overall Equipment Effectiveness

OEE % = Availability % × Performance % × Quality %

• Insure each metric excludes the effects of the other two (the negative

effects of an issue will be multiplied twice). For example, do not include equipment time loss in both Availability and Performance, only in Performance.

Availability = (Operating Time/Available Time)Time loss metrics should include:

• employee breaks• cleaning• changeover including lot/batch

change• equipment breakdown (not jams)• material shortages• preventative maintenance• exclude idle or scheduled downtime

Performance = (Total Products × Time)/Ideal Run Rate or (Total Products)/(Nominal Rate × Time)Speed loss metrics should include:

• equipment stops; jams and repetitive (roll change)

• track, but exclude product caused downtime

• track, but exclude lack of product input unless it is equipment related

• Total Products = (Product Output + Ejects + Rejects)

• Decide the Run Rate? Machine cycle setting, designed speed, or product throughput.

• Slowest machine on the line usually sets the Run Rate.

Quality = Good Products Out/Good Products InProduct loss metric:

• Initially count all rejected products as loss.

• Quantify rejects into the root causes, equipment related, commodity, and product quality or personnel.

• Rejects should be separated into rework (saved as good) and scrap. Decide how these are accounted for in the calculation and formula. How they are included is not as important as consistency, should you need to compare results from different studies.

Data CollectionThe collection of the data is probably the most time consuming part of the process, therefore it is best to have a well thought out plan before you begin.

Using a spreadsheet with a built in “Stop Watch” is a great convenience. Three “Data Logs” (see appendix) are suggested as a means of collecting the information that is needed. The “Logs” may be used serially or concurrently. For example, if a single machine is the object of the study, the “Each Machine Run Log” is all that is needed. Review and if possible use the data that is already being generated by the equipment; this could be entered directly into the “Log.”

1. “Line Time Log” – Overall Effectiveness of the Line?

a. The objective of this “Log” is to determine the overall OEE of the line and to separate the Availability and Equipment issues.

b. The duration of the “Log” will depend on the length of time it takes to cycle through the complete activities of the line. Typically, the time span is from start of one batch to the start of the next batch (including all lot change activities).

c. The number of cycles (rows in the “Log”) required is dependent on the consistency of the line while running a variety of products, shifts, and/or personnel changes. As a minimum, each SKU and shift requires a cycle in the “Log.”

d. Typical Chart Headings: Date, Shift, Product SKU, Run Rate, Time (Total, Clean/Lot, Changeover, Runtime, Repetitive (roll change)), Products (In and Out)

e. The calculated results (expressed as a percentage) will be the available time to run the equipment, the performance of the equipment, output product quality and the overall OEE of the line.

f. The tasks after this exercise are to evaluate the equipment, people, processes, and quality of incoming products.

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2. “Equipment Run Log” – Equipment Performance?

a. The objective of this exercise is to determine which machines are the most problematic.

b. List all of the machines on the line. c. Column Headings: Time (Start and

Stop), Machine listing, and Fault by Cause (Function, Personnel, or Materials)

d. The calculated results (expressed as a percentage) will be the percent of downtime caused by each machine as well as personnel and materials issues.

e. The task after this exercise is to determine which pieces of equipment need further evaluation.

3. “Each Machine Run Log” – Equipment Functional Issues?

a. The objective of this exercise is to determine which functions within a machine are the most problematic.

b. List all of the functions within the machine.

c. Column Headings: Time (Start and Stop), Function (full list), and Fault by Cause (Function, Personnel, or Materials)

d. The calculated results (expressed as a percentage) will be downtime by machine function as well as personnel and materials issues.

e. The task after this exercise is to determine which functions require improvement. The data will assist your diagnostic efforts of a problematic machine.

Report and AnalysisA “Summary Report” of the data will assist in the efficient mitigation of the issues that have been uncovered.

Present the data in an organized and precise manner. Assuming you have the data in a spreadsheet, graphs and charts may be produced. Graphical information is very informative for those reviewing the report.

Provide a list of proposed changes required (some mitigation tips):

1. Personnel and Process a. training b. preventative maintenance c. operating procedures d. changeover procedures e. location and movement of

commodities in the work area f. commodities loading aids g. warm up time of the equipment

2. Equipment a. buffers – smooth functioning b. accumulators in the proper location c. speed increases down the line

(accumulation) d. eject or reject without stopping e. proper location of surge controls f. modification to safeguarding

system g. accuracy of changeover (time from

last product to first good product) h. reduce time of repetitive roll

change i. update kits for equipment – contact

manufacturer j. new equipment, designed for high

OEE

3. Commodities a. carton/case design (flaps, notches,

scores, board thickness) b. storage of commodities (reduce

warpage, humidity) c. inserts: folding, tabbing, gluing and

storage in trays d. trays: denesting lugs, silicon

release e. labels: web, cutting through liner,

spacing on web f. A price increase in commodities

may have a huge payback.

Provide a budgetary cost of each change (include lost time to implement) and the increase in revenue due to each improvement (more effective than cost savings). Note the “Revenue per Unit” in the “Line Time Log”; this goes to the issue of increasing revenue without adding resources or time.

After implementation changes are made to the line, repeat the study to verify the results and/or provide even further improvements.

What is a good number for OEE?It is very difficult to find industry information that is meaningful due to the inconsistency of how and what data is produced. The important issue is to use consistent metrics within your organization when making a comparison. There are indications that an average OEE for a pharmaceutical line is somewhere between 15% to 45%, whereas a world class line may have an OEE of 67%. Again, this information is subjective.

ConclusionIncreasingly used within purchase specifications of equipment, OEE can be used to improve productivity of a packaging line, increasing output and profitability. While most of the information within the industry is centered on larger complex systems, this Knowledge Brief provides the basic concepts of OEE, particularly its application to operations associated with a primary or secondary packaging line located in a pharmaceutical area. An entry level OEE study can be done with a simple spreadsheet. The mere act of organizing the spreadsheet contributes to an understanding of the metrics of what and how data is best measured in a particular situation.

For Further InformationFor more detailed and related information, the following ISPE resources are available:

Communities of Practice (COP):• Visit the Packaging COP for the

most current and up-to-the-minute discussions on the topics discussed in this Knowledge Brief and other related topics.

http://www.ispe.org/packagingcop• Visit the Operations Management

COP for further information on OEE. http://www.ispe.org/omcop

About the AuthorMel Bahr has 46 years of experience in designing and manufacturing, helping to produce more than 35,000 pieces of packaging machinery. He founded MGS

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Machine Corporation more than 39 years ago and is active in sales, applications and R&D for the family operated business. He holds a number of patents for both equipment and processes. He is a past Chairman of PMMI (Pack Expo shows), Chairman of the PMMI/ANSI standards writing committee, a core Team member of JETT, Chairman of the ISPE Packaging COP and a long time member of ISPE. •