a functional approach to fixing flow oscillation

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This article was downloaded by: [University of Alberta] On: 26 October 2014, At: 14:25 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Quality Engineering Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/lqen20 A Functional Approach to Fixing Flow Oscillation Jeremy Hammond a , Angela Haiss a , Shawn Lavigne a , Beverly Daniels a & John Allen b a IDEXX Laboratories, Inc. , Westbrook , Maine b The New Science of Fixing Things, Ltd. , Portsmouth , New Hampshire Published online: 02 Sep 2013. To cite this article: Jeremy Hammond , Angela Haiss , Shawn Lavigne , Beverly Daniels & John Allen (2013) A Functional Approach to Fixing Flow Oscillation, Quality Engineering, 25:4, 385-391, DOI: 10.1080/08982112.2013.790739 To link to this article: http://dx.doi.org/10.1080/08982112.2013.790739 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions

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Page 1: A Functional Approach to Fixing Flow Oscillation

This article was downloaded by: [University of Alberta]On: 26 October 2014, At: 14:25Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

Quality EngineeringPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/lqen20

A Functional Approach to Fixing Flow OscillationJeremy Hammond a , Angela Haiss a , Shawn Lavigne a , Beverly Daniels a & John Allen ba IDEXX Laboratories, Inc. , Westbrook , Maineb The New Science of Fixing Things, Ltd. , Portsmouth , New HampshirePublished online: 02 Sep 2013.

To cite this article: Jeremy Hammond , Angela Haiss , Shawn Lavigne , Beverly Daniels & John Allen (2013) A FunctionalApproach to Fixing Flow Oscillation, Quality Engineering, 25:4, 385-391, DOI: 10.1080/08982112.2013.790739

To link to this article: http://dx.doi.org/10.1080/08982112.2013.790739

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) containedin the publications on our platform. However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor and Francis shall not be liable forany losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use ofthe Content.

This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Page 2: A Functional Approach to Fixing Flow Oscillation

A Functional Approach to FixingFlow Oscillation

Jeremy Hammond1,

Angela Haiss1,

Shawn Lavigne1,

Beverly Daniels1,

John Allen2

1IDEXX Laboratories, Inc.,

Westbrook, Maine2The New Science of Fixing

Things, Ltd., Portsmouth, New

Hampshire

ABSTRACT An automated instrument for veterinary diagnostics utilizes a

positive displacement syringe pump to move fluid within the system. Large

fluctuations in flow rate have been identified in some instruments, resulting

in system error flags. A problem-solving approach is described to show

the methodology used to understand and mitigate the failure. Multiple

problem-solving tools were incorporated where appropriate to solve this

problem. Measurement systems analysis and assembly=disassembly were

used to focus the investigation to the point where it was clearly determined

that the assembly process impacted the failure mode across the full range of

measured results. Structural and functional decomposition techniques

were used to identify the causal mechanism for the failure, leading to several

possible resolutions.

KEYWORDS assembly-disassembly, functional decomposition, measurement

systems analysis, source-load model

INTRODUCTION

An automated veterinary diagnostic instrument creates dilutions and

moves fluids utilizing a syringe pump. The syringe is mechanically linked

to a lead screw, which is driven by a geared pulley, as shown in Figure 1.

The gear pulley is coupled to a drive pulley by a timing belt. A stepper

motor increments rotation of the drive pulley, moving the belt and thus

the plunger as a function of the angular displacement and pitch of the lead

screw.

The flow from the syringe pump, shown in Figure 2, has an oscillating

pattern that causes a system fault when the flow oscillates with extreme

amplitude. This failure mode results in yield loss and rework.

PROBLEM-SOLVING APPROACH

The first step is to make sure that the measurement system is capable of

supporting the diagnostics by characterizing precision (repeatability) and

accuracy of the test device. A measurement systems analysis (MSA; Wheeler

and Lyday 1988) was performed, with results shown in Figure 3. The Y-axis

in Figure 3 is the quantitative value of the oscillation amplitude depicted in

Figure 2.

Address correspondence to AngelaHaiss, IDEXX Laboratories, Inc., 1IDEXX Drive, Westbrook, ME 04092.E-mail: [email protected]

Quality Engineering, 25:385–391, 2013Copyright # Taylor & Francis Group, LLCISSN: 0898-2112 print=1532-4222 onlineDOI: 10.1080/08982112.2013.790739

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This MSA procedure consisted of selecting multiple

pairs of instruments demonstrating the limits of flow

rate variation, pairing one high and one low instru-

ment and testing them iteratively and randomly.

The within-instrument scatter was small with respect

to the captured variation between high and low instru-

ments. The problem was repeatable within an instru-

ment and failing and functional instruments were

distinctly different, as exhibited in Figure 3. Probabilis-

tic confirmation of the measurement system provided

the confidence to move ahead with the search.

The next step was to identify the component(s) in

selected instrument pairs that drive the variation in

flow oscillation. This was a probabilistic approach

exploiting the power of paired instruments at either

end of the population tails in conjunction with a less

commonly used diagnostic approach, often called

effect-to-cause (Dale 1958). The flow rate variation,

shown in Figure 3, was used to identify instruments

at the population tails. The first step was a confir-

mation test that the problem persisted after a

disassembly–reassembly (Ott 1953) between high and

low instruments. The first action in the disassembly–

reassembly approach was to take the system apart

down to a predetermined granularity and reassemble

the system, keeping all parts contained within the

instrument. If the results were consistent with the

baseline data for each instrument, then subassembly

exchange commenced. In this instance, the instru-

ment assembly process was assumed to be low risk

so the initial step of removing and reinstalling the

pump was skipped. The risk was minimized because

the next step in the exchange procedure was to

return the pump to its original instrument for confir-

mation and, in effect, complete the disassembly–

reassembly step. Confirmation that the problem

was not attributed to the installation of the pump

was obtained when the pump assemblies were

returned to their original instruments and the large

flow rate variation reverted to the baseline levels.

FIGURE 2 Flow rate variation produced by positive-

displacement syringe pump: (a) nominal flow rate variation and

(b) significant flow rate variation from a failing pump.

FIGURE 1 Concept diagram of positive-displacement syringe

pump. (Color figure available online.)

FIGURE 3 Measurement systems analysis.

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At this point, the pump was broken down further to

the syringe drive, shown in Figure 1. The syringe

drive portions of the pumps were then interchanged

between pairs and the high flow rate variation

followed the syringe drive. Figure 4 shows that the

syringe pump was the driving factor for failure within

the instrument, and the syringe drive was the driving

factor for failure within the pump.

After narrowing the potential causal components

down to the syringe drive system, further disassembly–

assembly showed that the assembly method had a

large impact on performance (Figure 5).

Taking the syringe drive system apart and putting it

back together involved removing and replacing

everything up to and including the belt. Retesting

showed a change in flow oscillation amplitude, driven

by the assembly. Given that this was before the parts

were exchanged between pairs, the difference could

not be attributed to any component. In other words,

the full range of performance variation was captured

with the same parts. Therefore, the causal mechanism

could not be the parts alone. At this point another

diagnostic tool was required to move forward.

The lack of repeatability after disassembly–

reassembly was an important clue regarding the fail-

ure mode. In addition, the frequency and shape of

the oscillating signal tied directly to the syringe drive

system’s physical and mechanical properties. This

information identified that the source of the problem

centered on storage and release of potential energy.

Concluding that the problem was in the assembly

process pointed the problem-solving approach to

a functional decomposition method. In order

to understand what was really happening with this

pump failure mode, a source-load model was

applied, as shown in Figure 6 (The New Science of

Fixing Things 2011).

The Thevenin-Norton source-load model describes

that any complex electrical system can be graphically

represented with a power supply, a load, and a

resistor (The New Science of Fixing Things 2011).

The way the components are wired depends on

whether the power supply is a voltage source (Theve-

nin wires the load and resistor in series) or current

source (Norton wires the load in parallel). Any system

that operates based on energetic interactions, regard-

less of the domain, can be represented in this simple

but powerful way, as long as a few simple rules are

followed. One of those rules is that the flow of energy

is described by two conjugate variables, which, when

multiplied together, yield watts. Conjugate variables

for a few domains are volts and amps, pressure and

flow, and torque and angular displacement (The

New Science of Fixing Things 2011). The first variable

in each pair is the effort variable, e, and the second

FIGURE 6 Source-load model (The New Science of Fixing

Things 2011).

FIGURE 5 Assembly process affects pump performance and

failure.

FIGURE 4 Assembly–disassembly testing.

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variable is the flow variable, f, represented in Figure 7.

Source-load is a powerful diagnostic tool when applied

across multiple domains and permits useful energy

accounting by employing SI units. The diagnostics

require little more than separating the ideal input

power into that consumed by the load and that lost

to the source impedance. The solution typically lies

in reducing the impedance and thus the energy

consumption. The source-load model is based on

making machines use less energy. The second law of

thermodynamics indicates that the more efficient the

machine, the better it runs and the longer it lasts.

Source-load shows that efficiency is often the key to

improvement, not component variation reduction.

Probabilistic decomposition requires multiple sam-

ples for comparison, but the source-load approach

calls for only one poor performer. The fundamental

question is ‘‘What is happening and how is this sup-

posed to work?’’ The model shown in Figure 1 is a

good basis to begin analysis for this failure.

The function of each subsystem is written using a set

of rules developed by Hartshorne and Allen (The New

Science of Fixing Things 2011). There are only seven

functions (supply power, dampen power, contain

energy, release energy, transmit power, direct power,

and convert power) performed by machines and only

three properties (inertance, compliance, and resist-

ance) that govern functional behavior. The functions

and properties are used to build the diagram shown

in Figure 8. The arrows always show the direction of

power flow. The notation above the arrow is the effort

variable and below the arrow is its conjugate flow

variable from the same domain.

Once the E-FAST diagram (Bytheway 2007) is

finished, functions can be isolated and tested in

informative ways. Altering the system inputs and

monitoring the response can often provide direct

insight to performance. For example, in stepper

motors the torque drops off rapidly as the velocity

increases (Solarbiotics 2011). This torque decay is

not as radical in permanent magnet DC motors.

The oscillation frequency and amplitude provide sig-

nificant information regarding pump performance. Is

motor stepping the source of the oscillations? To

answer this question, a 24V DC motor was substi-

tuted for the stepper motor, but the flow oscillation

persisted. Because motor stepping was not the

causal mechanism, the source of the oscillations

could not be from the functions shown in Figure 8.

The next piece evaluated was the fluidic load at

the syringe. It was simple and fast to remove the

syringe, essentially removing the functions covered

in Figure 9. The oscillating pattern and amplitude

remained despite syringe removal. At this point,

Figures 8 and 9 were ruled out (the failing conditions

were not significantly impacted by the motor or

fluidic load because the oscillating pattern and

amplitude remained). The only remaining functions

were performed by the belt.

Figure 10 shows a diagrams of how the power gets

from the pulley into the belt as potential energy and is

then released. This represents an effort-based serial

power transmission, with effort dropped as the belt con-

tains and releases energy, and the parasitic loss of effort.

In order to understand belt function, the system

was evaluated utilizing a range of belt tensions and

stepper motor speeds. A narrow band of belt tension

FIGURE 8 E-FAST shows power to the first gear, up to the belt.

x is a function of switching speed, I is a function of impedance.

FIGURE 10 Power from the stepper motor to the second

pulley.

FIGURE 7 Effort and flow workspace (The New Science of

Fixing Things 2011). (Color figure available online.)

FIGURE 9 Pulley to the syringe.

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was identified that turned out to drive a standing

wave. A standing wave is an energy sink, an undesir-

able element of contain-and-release potential energy

functions. Likewise, a small range of stepper motor

speeds resulted in increased flow rate variation,

shown in Figure 11.

CAUSAL EXPLANATION

The system proved to be operating in a resonance

condition, as shown in Figure 11, for one particular

belt tension. Resonance occurs when a system in

motion with a small vibration near the fundamental

frequency of the system grows to large amplitude

(HyperPhysics 2011). Resonance has been shown

to occur in belt-driven systems (Stevens 2011) when

the fundamental natural frequency of the belt

matches the motor drive or load frequency. The

power in understanding the physics of the system

yields a number of options to mitigate the failing

condition. For example, modifying the tension or

length of the belt will change its natural frequency.

Modifying the drive speed of the motor or the mech-

anical impedance of the load will also move the sys-

tem away from resonance. The causal explanation

requires knowledge of functional decomposition in

order to analyze system behavior in a way that is

consistent with first principles, sound diagnostics,

and convergence.

ELIMINATING THE PROBLEM

Once a valid causal explanation for system

behavior has been identified and tested, technicalFIGURE 13 Potential schematic without belt to remove source

of resonance.

FIGURE 12 Direct drive system without timing belt. (Color

figure available online.)

FIGURE 11 System resonance response by varying motor

drive speed.

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and business decisions can be made to determine

appropriate modifications to eliminate failures. In

order to mitigate resonance, the characteristics of the

belt can be changed, the mechanical impedance of

the load can be changed, or the motor drive speed

can be changed, all while maintaining the syringe pump

in its current configuration. An alternative solution

would be to remove the belt drive, thus changing func-

tion dependencies. The decision on which avenue to

follow came from an analysis of cost of implementation,

time to implement, risk to the system, and physical lim-

itations related to the syringe pump and its application.

Directed testing can be performed quickly to confirm

any recommendations for actions. For reference, remov-

ing the belt and directly driving the lead screw by the

stepper motor (schematic shown in Figure 12; results

shown in Figure 13) removed the failing condition

(reduced oscillations were still present, driven by sec-

ondary factors).

The problem-solving approach described in this

article is summarized in Figure 14.

CONCLUSION

The role of scientists and engineers is to design

and manufacture products that are consistent with

the strategic objectives described at the outset of

this article. Fundamental operation is in the determi-

nistic world of first principles, supplemented and

complemented with probabilistic tools. Tools are

used in this process where they provide the largest

benefit and are halted at the point where a different

approach provides the best path toward under-

standing. This failure analysis included probabilistic

techniques to narrow the system down to the

smallest subassembly that yielded clear direction,

and then functional decomposition was incorpor-

ated to describe the system operation and identify

the areas that negatively affect performance. The

power in this solution is that the system is character-

ized and a number of approaches to mitigate the

failure are available and can be selected by business

merit.

ABOUT THE AUTHORS

Jeremy Hammond received a B.S. in Engineering

Physics from Embry Riddle Aeronautical University,

an M.S. in Engineering Physics from The University

of Maine, and a Ph.D. in Biosystems Engineering

from The University of Maine. He has experience

as the Director of Engineering at Sensor Research

and Development Corporation and is currently act-

ing as R&D Manager at IDEXX Laboratories with

emphasis on hematology and urinalysis instrumen-

tation systems.

Angela Haiss received a B.S. in bio-resource

engineering from the University of Maine and an

M.S. in biomedical engineering from Johns Hopkins

University. She has seven years of engineering

experience and is currently a Staff Engineer at IDEXX

Laboratories.

Shawn Lavigne studied Biology at the University

of Southern Maine and the University of New

England. He has experience as an IDEXX Labora-

tories Six Sigma Black Belt. He is currently a Process

Engineer at IDEXX Laboratories.

Beverly Daniels received a BS in electrical engin-

eering from Michigan Technological University.

She has thirty years of experience in Quality Engin-

eering, Six Sigma and Operational Excellence in a

variety of industries including Semiconductors, auto-

motive, aerospace and biomedical. She is currently

the Director of Operational Excellence at IDEXX

Laboratories.

John Allen received a B.A.Sc. from Gannon Uni-

versity and is a partner and founding member at

The New Science of Fixing Things.

FIGURE 14 Problem-solving approach utilized for the flow oscillation problem.

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REFERENCES

Bytheway, C. W. (2007). FASTCreativity and Innovation. FL: J. Ross Publishing.Dale, H. C. A. (1958). Fault finding in electronic equipment. Ergonomics,

1(4):356–385.HyperPhysics. (2011). Standing waves on a string. Available at: http://

hyperphysics.phy-astr.gsu.edu/Hbase/waves/string.html (accessedJanuary 20, 2011).

The New Science of Fixing Things. (2011). Source load model andE-function trifold. Available at: http://www.tnsft.org/restricted/resources/E-Functions%20Trifold%20080227.pdf (accessed January 20, 2011).

Ott, E. R. (1953). A production experiment with mechanical assemblies.Industrial Quality Control, 9(6):124–130.

Solarbotics Ltd. (2011). Industrial circuits application note stepper motorbasics. Available at: http://www.solarbotics.net/library/pdflib/pdf/motorbas.pdf (accessed January 20, 2011).

Stevens, D. (2011). Vibration analysis—Belt drive problems. Availableat: http://www.vibanalysis.co.uk/vibanalysis/belts/belts.html (accessedJanuary 20, 2011).

Wheeler, D., Lyday, R. (1988). Evaluating the Measurement Process,Knoxville, TN: SPC Press.

APPENDIX: VARIABLE DEFINITIONS

a Area

d Displacement

E Electromotive force

eZL Effort: impedance load

F Force

fs Flow: source

fZL Flow: impedance load

I Current

P Pressure

R Resistance

S Entropy

T Temperature

V Volume

v Velocity

ZL Load impedance

Zs Source impedance

s Torque

x Angular velocity

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