OPMA 317 CHAPTER 8 EXAM QUESTIONS WITH CORRECT ANSWERS LATEST UPDATE 2026

OPMA 317 CHAPTER 8 EXAM QUESTIONS WITH CORRECT ANSWERS LATEST UPDATE 2026 What are the effects of poor quality on an organization? - Answers Higher transformation costs (rework, scrap), lost sales (short term), lost reputation (long term), higher warranty costs (returns, repairs), and lawsuits. What is the three-stage quality management flow? - Answers Alarm bell (detect: checksheets, Pareto, scatter diagrams, control charts) → Investigate (root cause analysis, fishbone) → Prevent (process failsafes, checklists). How can quality be both very costly AND "free"? - Answers Cost of quality can reach 25% of revenue (goods) or 40% of operating expenses (services). But Crosby's "quality is free" means improving quality by shifting money from failure costs into control costs — no new money needed. What are the two big buckets in the cost of quality, and the tradeoff? - Answers Control costs (prevention + appraisal) and Failure costs (internal + external). Spending more on control drives failure costs down; the goal is to move spending from failure to control. Prevention vs Appraisal — define, with the checkstop example. - Answers Both are control costs. Prevention = proactive, stops defects before they happen (anti-drinking-and-driving campaign). Appraisal = inspection to catch defects (impaired-driving checkstop). What is failsafing (poka-yoke)? - Answers Creating a control condition where the customer or employee can only take the correct action while performing the process. Give examples of poka-yoke failsafes. - Answers Airplane bathroom light won't turn on until the door is locked; ATM makes you remove your card before dispensing cash; speed bumps; clearance bar before a parking garage; jet-ski kill-switch key tethered to the driver. In the cost of quality, how is a failsafe classified? - Answers As a prevention cost — it stops the problem from ever occurring. Why are checklists effective? - Answers They're cheap and efficient, formalize "lessons learned," share best practices, and the improvement is typically immediate and significant. How is AI used in quality monitoring? - Answers Data-driven predictive analytics to spot product failures and process/equipment problems before they happen, plus faster and more accurate audits and inspections. What is Six Sigma's goal? - Answers Reduce process variation until only 3.4 defects per million are produced. It provides a framework and methodology to analyze processes and reduce waste. What does DMAIC stand for? - Answers Define, Measure, Analyze, Improve, Control — the Six Sigma improvement methodology. What is a Six Sigma Black Belt? - Answers A certification for someone who leads process-improvement projects and teams. What is the PDCA cycle, and who developed it? - Answers Walter Shewhart's continuous-improvement cycle: Plan (the improvement), Do (implement it), Check (actual vs planned), Act (adjust so actual meets planned). What is ISO 9000? - Answers A series of international generic management-system standards. They are PROCESS standards, not product standards — they govern how processes are measured/documented, not specific product tolerances. Purpose: facilitate international trade. What is ISO 14000? - Answers Environmental management standards — minimizing an organization's harmful environmental effects and continually improving its environmental performance. What is ISO 26000, and how does it differ from 9000/14000? - Answers Guidance on social and environmental responsibility. Unlike 9000 and 14000, it is NOT a certification standard — it's a voluntary guidance tool ("good intentions to good actions"). What is Pareto analysis? - Answers Distinguishing the "vital few" (80/20 rule): rank events in decreasing order of frequency, then show a bar chart of frequencies plus a cumulative-percentage line. What is a scatter diagram? - Answers Plotting paired data points to visually interpret the relationship between two variables (e.g., wait time vs customer satisfaction). What is a fishbone diagram (and its other names)? - Answers A cause-and-effect / Ishikawa diagram — keep asking "why?" to find the root cause. Categories are the 5 Ms: Man, Material, Machine, Method, Measurement. Acceptance sampling vs SPC — define each. - Answers Acceptance sampling = a form of appraisal; accept/reject goods that already exist. Statistical Process Control (SPC) = a form of prevention; sets standards to signal adjustments while the good/service is being produced. Attributes vs variables data — and which chart each uses. - Answers Attributes = counted data (# of complaints, damaged/not) → p-chart. Variables = measured data (cm, kg, ml) → X-chart & R-chart. In "5 bags pulled 4 times daily," what are n and m? - Answers n = observations per sample = 5; m = number of samples = 4. The grand mean averages the sample means. What are the two measures of dispersion used? - Answers Range (largest X − smallest X) and standard deviation. What is the Central Limit Theorem in the QC context? - Answers For large enough n, the distribution of sample means tends toward normal even if individual observations aren't. Sample means have lower variability than, and the same mean as, the individual process distribution. Type I vs Type II error — define, including the risk names. - Answers Type I: sample says "problem" but it's actually OK → unnecessary stop; the Producer's risk. Type II: sample says "OK" but there's actually a problem → defect slips through; the Consumer's risk. How do quality strategy and control tightness relate to error types? - Answers High-Quality strategy avoids Type II errors → "tight" controls → more Type I errors. Low-Cost strategy avoids Type I errors → "loose" controls → more Type II errors. What is a control chart used for? - Answers To infer whether a process is in control or out of control, based on sample statistics plotted over time against a central value, UCL, and LCL. In control vs out of control — define, plus the key caveat. - Answers In control: process runs as usual, variation is only random (common causes). Out of control: variation is not purely random — assignable/special causes are present. Caveat: "out of control" does NOT mean bad output, just that the process isn't behaving as expected. Random vs assignable variation? - Answers Random (common-cause) variation is inherent and expected → in control. Assignable (special-cause) variation has a specific identifiable cause → out of control. Setting up a p-chart — the formulas. - Answers p̄ = total defectives ÷ (sample size × number of samples). Sp = √[p̄(1−p̄)/n]. UCL = p̄ + z·Sp; LCL = p̄ − z·Sp (if negative, set LCL = 0). In the p-chart example, why investigate points BELOW the LCL? - Answers A point above UCL = poor performance to investigate; a point below LCL = unusually GOOD performance — investigate to learn what went right and repeat it. Either way, the process is "out of control." X-chart & R-chart — what do they monitor, and when is the process in control? - Answers X-chart monitors central tendency (the average); R-chart monitors variability (the range). BOTH must be in control before the total process is in control. X-chart and R-chart control-limit formulas. - Answers X-chart: UCL = X̄̄ + A₂R̄, LCL = X̄̄ − A₂R̄. R-chart: UCL = D₄R̄, LCL = D₃R̄. A₂, D₃, and D₄ come from the factor table by sample size n. Besides a point beyond a limit, what other signals mean "stop & investigate"? - Answers Trends in one direction, consecutive points near the UCL/LCL, five consecutive points above/below the central line, and erratic behaviour.