AN INSTRUCTIONAL COMPUTER SIMULATION OF TAMPERING IN QC Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 123 AN INSTRUCTIONAL COMPUTER SIMULATION OF TAMPERING IN QC Dongping Nie, University of Utah Susan A. Chesteen, University of Utah ABSTRACT With increased availability of computers and more affordable plotting software in business schools, the task of teaching some of the important principles of quality control in an effective way is placed in a new perspective. This paper presents an innovative way of teaching the concepts of process variation and tampering using a computer simulation TAMPER. The simulation helps students visualize the effects of process tampering, a common problem in quality control. Aside from a brief account of the precursor experiment, we discuss program issues and simulation results as well as the benefits of TAMPER as an experiential learning tool in quality control. INTRODUCTION Some two thousand years ago the ancient Chinese philosopher, Laotsu, taught his pupils that: governing a big state is like cooking a small fish, you do not overdo it.’ Recently this same line of reasoning found its way into the business world under a new name, tampering (Deming, 1986; Gitlow, et.al., 1989). As one of the pioneers in the field of quality control W. Edwards Deming put it, "if anyone adjusts a stable process to try to compensate for a result that is undesirable or for a result that is extra good, the output that follows will be worse than if he had left the process alone” (Deming, 1986). It is no secret to most practitioners in the business world that overcontrol. of processes occurs often when management attempts to improve these processes based on the discovery of just one defective or lust one customer complaint without profound knowledge of the consequences. Loss to an organization due to tampering can be unexpectedly costly. Boardman et. al. (Gitlow et. al., 1989) proposed the following table-top experiment to help visualize the effects of tampering with a process. The physical requirements for the experiment include a funnel, a marble that will fall through the funnel, a flat surface, a pencil for marking the landing places of the marble, and a holder for the funnel (Figure 1). The marble is dropped repeatedly through the funnel and for each drop its position is marked. Five rules for adjusting the funnel between consecutive drops are used to demonstrate the effects of different adjustment patterns on the final outcome. However, as an experiential method for teaching the effects of tampering during one class period, this experiment has several shortcomings. The actual conduct of this experiment is virtually impossible due to its time-consuming nature and the difficulty in accurately recording and plotting all landing points. A more viable alternative to demonstrate this same concept of tampering with a process is to utilize computer simulation. The use of computer simulations as teaching tools has proliferated in business schools (Frazer, 1984; Naylor, et.al., 1966; Sanders et.al., 1978; Sekely, 1984) In particular, the application of simulation techniques in quality control has proven to be both valuable and efficient in educational settings. For example, Frazer developed and successfully utilized a computer laboratory exercise involving student decision-making for a production process. Following the lead of instructors such as Frazer, the authors created a computer simulation TAMPER for classroom use to assist in teaching several principles in Quality Management, a newly developed course designed for MBA and Ph.D. students. A broad range of topics were treated in the course including such subjects as quality management from a strategic point of view, general concepts of quality control, economic analysis of quality costs, and a technical attack on product quality to detailed methods of statistical quality control. The control of variation is a major task of quality control in production. in addition to the manual production of control charts and plots, we also asked our students to perform exercises using QSOM (a software of Quantitative Systems for Operation Management). To further extend the experiential learning aspect of the course, we created our own computer program TAMPER to simulate the effect of tampering with a production process. The primary objectives of the simulation TAMPER are to help students understand the concept of variation in QC, to investigate the effects of process tampering, and to appreciate the advantages of computer simulation as an experiential learning method. DESCRIPTION OF TAMPER TAMPER is a computer program that simulates the act and consequences of tampering with a process, a common quality control problem. It consists of two FORTRAN programs: (1) “RWALK.FOR which generates data points representing the landing places of the marble in the previously described physical experiment and (2) “PLOT.FOR” which graphically presents the results of RWALK.FOR in the form of scatter plots and control charts. FORTRAN was the chosen language because of its flexibility in coding, its versatility in graphics, its rich library, and its wide acceptance by students (Naylor, et.al., 1966; Pidd, 1984; Pritsker, 1986). “RWALK.FOR” uses an IMSL (International Mathematical and Statistical Library) subroutine RNSPH. RNSPH generates a random number vector, each component of which locates an arbitrary point on a unit circle. Users of our program may incorporate any other reliable random number generator to replace RNSPH if so desired. It takes less than 5 seconds to generate 100 data points on a VAX 11/750. Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 124 "PLOT.FOR” is more system dependent than “RWALK.FOR’ due to the existence of a variety of plotting software and hardware. HANDYPAK was employed in our example because of its availability. DESCRIPTION OF RULES The pattern of data points generated by “RWALK.FOR” is governed by the rules used in the design of the program. The first four rules closely follow Boardman’s original design. The fifth rule is actually a variation of rule 3. Conceivably, interested readers can invent additional rules and attempt to discover their perspective impact on the final outcomes. The five rules we used are: Rule 1: Set the funnel over the target at (0,0) and leave the funnel fixed through all 100 drops. The final outcome using this rule is displayed in Figure 2 which shows the pattern of points forming a ring The fact that all 100 points are not located at (0,0) is evidence of the presence of a limited amount of variation without any tampering. Rule 2: The funnel, is set over the target at (0,0) prior to the initial drop; let (Xk, Yk) represent the point where the marble dropped through the funnel comes to rest on the surface. Rule 2 states that the funnel should be moved a distance (-Xk, -Yk) from its last resting point. From Figure 3, we can see that the ring generated by Rule I was made dimmer’ and less defined. This demonstrates that there is more variation present due to the tampering effect. Rule 3: The funnel is set over the target at (0,0) prior to the initial drop; let (Xk, Yk) represent the point where kth marble dropped through the funnel comes to rest on the surface. Rule 3 states that funnel should be moved a distance (-Xk, -Yk) from the target (0,0). A bow tie shaped scatter plot is generated by this rule (Figure 4). The appearance of this pattern provides even more evidence of the phenomenon of variation. Rule 4: The funnel is set over the target at (0,0) prior to the initial drop; let (Xk, Yk) represent the point where kth marble dropped through the funnel comes to rest on the surface. Rule 4 states that the funnel should be moved to the resting point on the surface (Xk, Yk). A rather irregular shape (Figure 5) appears as a result of this rule. Rule 5: The funnel is set over the target at (0,0) prior to the initial drop; let (Xk, Yk) represent the point where kth marble dropped through the funnel comes to rest on the surface. Rule 5 states that the funnel should be moved distance (-Xk/2,,-Yk/2) from the target (0,0). This is a modification of Rule 3 where the distance of the moves has been reduced by one half. In sharp contrast with the results from Rule 3, the data points are much more confined (Figure 6). This pattern indicates that less variation results if the magnitude of the tampering is reduced in each step. EVALUATION OF OUTCOMES USING CONTROL CHARTS The scatter plots only provide a general idea of the resultant variations. To further understand the impact of tampering, these criteria are provided by the PLOT.FOR in the form of control charts. Control charts for individual, units are special statistical charts for process control where sample size equals one. This occurs frequently when automated inspection and measurement technology are used and every unit manufactured is analyzed (Montgomery, 1985). Since the subgroup consists of single measurement, there is no variation within the subgroups themselves. Therefore, the estimate of the process variation has to be derived from the variation between the successive observations. The control chart has two parts: one for the process mean and one for the process variability. DISCUSSION OF RESULTS The two variables, X and Y are symmetric. The process for constructing and analyzing the control charts for the variable X is the same as for Y. So we have chosen to construct control charts for X as an illustration of the use of control charts in the analysis of the resultant variations. Figures 7-11 display and R control chars for X derived by TAMPER subject to the various rules. The reader may observe from an analysis of these figures that they reveal, unequal amounts of process variation. Each control chart is distinctive and allows the reader to detect whether the process is in control. The following discussion assists in the discrimination process and the interpretation of the results. Basically, the process for Rule I is within the R control limits and X control limits (Figure 7). However, there are three points slightly above the upper R control limit. Management’s use of the first rule demonstrates an understanding of the distinction between special and common variation, and the different types of managerial action required for each type of variation (Gitlow, et.al., 1989). It is clear that control charts for rule 2 (Figure 8) show more variation than those for rule 1. The R control chart for rule 3 (Figure 9) shows a significantly different pattern from the other Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 125 R-charts. Even though the X chart is still within the limits, the process is out of control. The R control chart signals that managers and operators with inadequate knowledge who “attempt” to reduce the variation by somehow •“compensating for what is lacking in the previous step will ultimately create more variation through this effort. The R chart for rule 4 is entirely within the control limits (Figure 10) because of the way the points are generated (each point is not farther away from its previous point by one step size). Though the X chart shows no points off the limits, a8 a practical rule, a run of more than seven consecutive points having the same signs indicates the process is out of control. Also, the scatter plot along with the X chart reveals that the mean deviation from the origin point grows as the square root of the number of data points (Spitzer, 1976). Deming called this phenomenon ‘a man who matches color from the match to batch for acceptance of material, without reference to the original swatch" (Deming, 1986). Setting the current inspection policy based on the previous record is an example of rule 4. Recall that Rule 5 is an alteration of Rule 3 where there is a lessor degree of tampering and therefore less variation is produced Control charts (Figure 11) produced using these two different rules are excellent examples for visualizing how the effects of variations are related to the degree of the tampering. SUMMARY Tamper is a computer simulation, which provides students with a hands-on laboratory experience for the control of variation. Through the visualization of the effects of overcontrol, students gain a better understanding of the concept and causes of variation. For classroom purposes, The computer simulation of the experiment was found to be both efficient and effective. We first introduced TAMPER to the students in a classroom presentation focussed on the use of simulation as a quality control tool. Students were interested in the idea of the funnel experiment as well as the computer simulation. Their immediate reaction was to ask which programming language was used arid whether they could run the computer simulation by themselves. At this suggestion, we refined and improved the program to make it more user friendly. Because classroom time was a limiting factor, we only showed the students the whole procedure of operating this program. They were fascinated by the moment when random points began appearing on the color monitor screen. The feedback we received has prompted us to install it for future use for both teaching and research. TAMPER is expeditious, flexible, and inexpensive It accomplishes the same goals as the actual physical experiment and its results are more accurate. Students commented that it was a vivid and direct way to learn the concept of tampering. The results of this simulation illustrate the effect of overadjustment of a process. The use of this Simulation should help a person realize that attempting to correct or improve a process without profound knowledge of the process will only exacerbate the problems. Improvement of the process cannot be achieved through tampering. REFERENCES Deming, W. Edward (1986), Out of the Crisis, Cambridge, Mass.: MIT Center for Advanced Engineering Study, 327-32. Frazer, Ronald (1984), ‘A Microcomputer Laboratory in Quality Control", Developments in Business Simulation and Experiential Exercises (ABSEL), 11, 194-197. Gitlow, Howard, Gitlow, Shelly, Oppenheim, Alan, & Oppenheim, Rosa (1989), Tools and Methods for The Improvement of Quality, Richard 0. Irwin, Inc. Montgomery, Douglas C.(1985), Statistical Quality Control, John Wiley and Sons. Naylor, Thomas H., Balintfy, Joseph L., Burdick, Donald S., and Chu, Kong (1966), Computer Simulation Techniques, John Wiley & Sons, Inc. Pidd, Michael (1984), Computer Simulation in Management Science, John Wiley & Sons. Pritsker, A. Alan B. ( 1986), Introduction to Simulations and Slam II, Systems Publishing Corporation, West Lafayette, Indiana. Reitman, Julian (1971), Computer Simulation Applications, John Wiley & Sons, Inc., 1971. Sanders, Susan, Speedie, Stuart, et al. (1978), The Computer in Educational Decision Making, Time Share, Houghton Mifflin Company. Sekely, William S.( 1984), "Impact of Economic Patterns on Student Performance in Computer Business Simulation Games, Developments in Business Simulation and Experiential Exercises (ABSEL), 11, 10-13. Spitzer, Frank Ludvig (1976), Principles of Random Walk, Springer-Verlag. Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 126 Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 127 Table of Contents Volume 17, 1990 The Impact of Decision Support Systems on the Effectiveness of Small Group Decisions - Revisited The Relationship Between Financial Performance and Other Measures of Learning on a Simulation Exercise Use and Effectiveness of an Analogy-Based Expert System Suggestions for Computerized Business Authors Dealing with Power: An Experiential Exercise Using Movie and Personal Diary Analysis Techniques A Model for Developing Student Skills and Assessing Outcomes Through Outdoor Training Computer-Aided Exercises Versus Workbook Exercises as Learning Facilitator in the Principles of Marketing Course An Exposition of Guilford's Si Model as a Means of Diagnosing and Generating Pedagogical Strategies in Collegiate Business Education Formal Planning and Simulation Team Performance: A Cross Sectional Approach Cases: Real Organizations in Real Time in the Classroom An Empirical Investigation of the Internal Validity of Marketing Simulation Game An Empirical Evaluation of the Pedagogical Value of Playing a Simulation Game in a Principles of Marketing Course Factors Affecting Effective Teaching of Strategic Planning: Some Preliminary Evidence An Experiential Exercise for Learning About the Relationship Between Organizational Form & the Project Management Process Accounting Communication Skills can be Taught in the Auditing Course Modeling Cost Functions in Computerized Business Simulation: An Application of Duality Theory and Sheppard's Lemma A Life Cycle Analysis of Decision Making for a Strategic Management Team What's the Problem? A Dynamic Model for Teaching Problem Solving Skills Experientially International Currency Fluctuations: Money$im, A Simulation Superstores: A Specialized Retailing Simulation Within a Specialized Marketing Curriculum Factors Affecting Student Perceptions of Learning in a Business Policy Game VC + EL = VL The Name Game: An Experiential Exercise in Intergroup Relations The Effects of Experiential Accounting Work Experience on Student Performance in Intermediate Accounting Courses The Results of Using the Experiential Activity Group Performance Evaluation in a Business Policy Setting Using a Legal Database to Describe the Legal Environment of Marketing (and Business) Matching Environmental Uncertainty and Organizational Configuration An Instructional Computer Simulation of Tampering in QC Executive Evaluation of Student Learning in the Looking Glass Simulation Group Personality Composition and Total Enterprise Simulation Performance An Expert System for Selecting Analytical Techniques for Analyzing Marketing Research Data Effects of Cognitive Styles on Responses in an In-Basket Simulation A Psychometric Analysis of Kolb's Revised Learning Style-Inventory Selecting and Developing Experiential Exercises Using Movies Application of a Real-World Strategic Management Model in the Classroom Demand Equations which Include Product Attributes Consumption as the Objective in Computer-Scored Total Enterprise Simulations The Effects of Decision Format and Evaluation on Simulation Performance, Decision Time, and Team Cohesion The Effects of Computer Related Assignments on Student Performance in Business Administration The Money Game: A Dynamic Simulation Including Random Shocks for Money and Banking Courses Methods for Evaluating Performance on Business Simulations: A Survey The Effects of Synergogy on the Policy Course: Significant Improvements in Student Learning and Teacher Evaluation Conditions and Outcomes of Trust in a Two-Person Bargaining Exercise Bankgame Enhancing Computer Business Simulation with the Use of VGA Graphics An Experiential Approach to Entrepreneurship An Advanced Simulation Method (ASM) for Multiple Objective Problems The Influence of Experiential learning Techniques on Student Recognition of Non-Primary Learning Styles Negotiating Mergers and Acquisitions: A Cocktail Napkin Approach Identification of Unintended Effects in Experiential Laboratory Exercises An Experimental Comparison of Paper and Pencil and Computer Aided Decision Support Tools Porting a Simulation from the IBM World to the Macintosh World A Transaction Cost Analysis of Experiential Learning The Development of Experiential Exercises for Courses in Entrepreneurship and Small Business Management The Assessment Center as and Experiential Classroom Exercise Pricing Strategy Algorithms for Playing Business Simulations Organizational Structures for International Operations: An Experiential Activity Simulation Emphasis in the Business School Capstone Course An Integrated Approach to Computerizing the Business Curriculum Cross-Cultural Business Negotiations Exercise Organizational Socialization and Gender Differences in Students at Work Understanding Student Work Experience: A Content-Analytic Approach Introducing Executive MBA Programs with Management Games An Analysis of Improvement in Business Decision Outcome with Sequential Use of Two Simulation Games Teaching Business Policy Utilizing Mass Lecture and Individual Case Labs Potholes Along the Road to Evaluating Learning Outcomes: The Case of Outdoor Management Training Experiential Learning for Interior Design Students: Using CADD, Lotus 1-2-3, and Wordperfect Cognitive Learning Using a Computer-Based, Qualitative Interactive Business Simulation Sex Discrimination: Does the Woman get the Job or Does the Best Man Win? A Search for Visual Aids to Support Experiential Learning Through the 1990's An Experimental Analysis fo the Effectiveness of Student Role-Playing in Sales Training How to Have Students Learn from their Term Projects Self-Evaluation Exercise (SEE): An Assessment of Class Contribution A Study of the Influence of Team Formation on Attitudes and Performance in Management Games A Hardware Based CIM Simulation Laboratory Model Test Substance Abuse in Organizations Micro Computer Training Models Teaching Forecasting, Cash Budgeting and Inventory Model Building Using SBTools A Comparison of the Effects of Experiential Learning Activities and Traditional Lecture Classes An Adjunct Writing Instruction Assistant, The Computer; With an Illustration Classroom Software for ABC Analysis Utilizing Information Processing Technology to Enhance the Business Policy Simulation Experience Progressive Cases Realistic Job Previews Vs. Traditional Job Previews: Experiencing the Differences and Understanding the Consequences Investment Analysis Using the Pragmatic Multiplier Approach A Computer Simulation Interface for Competitive and Firm Analysis Self-Assessment of Ethical Decision Making Predispositions Preparing Managers for Overseas Assignments An Inquiry into Japanese Marketing: Workshop on Teaching Japanese Marketing The Performance Appraisal Feedback Interview: A Role Play for Human Resources Management Teaching Counselor Selling techniques Using Experiential Techniques to Teach International Topics International Management Simulation Gaming: Current Status and Future Developments A Realism Comparison of Simulation Technologies/Methodologies A Time-Efficient Game to Illustrate Concepts Taught in Management Courses and Management Development Programs Teaching the Management of Technology The Concept of Face and the Applicability of Experiential Exercises in an Oriental Culture's