Chapter 8: Quality Management © Holmes Miller 1999.

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Presentation transcript:

Chapter 8: Quality Management © Holmes Miller 1999

Importance of Quality Costs & market share Market Gains Reputation Volume Price Lower Costs Productivity Rework/Scrap Warranty Improved Quality Increased Profits What is quality??

Not just the mean is important, but also the variance Need to look at the distribution function The Concept of Consistency: Who is the Better Target Shooter?

Common Cause Variation (low level) Common Cause Variation (high level) Assignable Cause Variation Need to measure and reduce common cause variation Identify assignable cause variation as soon as possible Two Types of Causes for Variation

Funnel Experiment (Deming) Tampering with a stable system only increases the production of faulty items and mistakes. äTampering is taking action based on the belief that a common cause is a special cause. Improvement of a stable system nearly always means reduction of variation. One necessary qualification of anyone in management is stop asking people to explain ups and downs that come from random variation.

Time Process Parameter Upper Control Limit (UCL) Lower Control Limit (LCL) Center Line Track process parameter over time - mean - percentage defects Distinguish between - common cause variation (within control limits) - assignable cause variation (outside control limits) Measure process performance: how much common cause variation is in the process while the process is “in control”? Statistical Process Control: Control Charts

Define control limits Constants are taken from a table Identify assignable causes: - point over UCL - point below LCL - many (6) points on one side of center In this case: - problems in period 13 - new operator was assigned Control Charts: The X-bar Chart

Attribute Based Control Charts: The p-chart

Process capability measure 33 Upper Specification Limit (USL) Lower Specification Limit (LSL) X-3s A X-2s A X-1s A XX+1s A X+2sX+3s A X-6s B XX+6s B Process A (with st. dev s A ) Process B (with st. dev s B ) x  C p P{defect}ppm 1  ,000 2  ,500 3  ,700 4    2.002x The Statistical Meaning of Six Sigma Don’t confuse control limits with specification limits: a process can be in control, yet be incapable of meeting customer specs

Pareto Analysis Browser error Number of defects Order number out off sequence Product shipped, but credit card not billed Order entry mistake Product shipped to billing address Wrong model shipped Cumulative percents of defects

1. Management Responsibility 2. Quality System 3. Contract review 4. Design control 5. Document control 6. Purchasing / Supplier evaluation 7. Handling of customer supplied material 8. Products must be traceable 9. Process control 10. Inspection and testing 11. Inspection, Measuring, Test Equipment 12. Records of inspections and tests 13. Control of nonconforming products 14. Corrective action 15. Handling, storage, packaging, delivery 16. Quality records 17. Internal quality audits 18. Training 19. Servicing 20. Statistical techniques Examples: “The design process shall be planned”, “production processes shall be defined and planned” How do you get to a Six Sigma Process? Step 1: Do Things Consistently (ISO 9000)

Minimum acceptable value Maximum acceptable value Target value Quality Good Bad Performance Metric Target value Quality Loss Performance Metric, x Loss = C(x-T) 2 It is not enough to look at “Good” vs “Bad” Outcomes Only looking at good vs bad wastes opportunities for learning; especially as failures become rare (closer to six sigma) you need to learn from the “near misses” Catapult: Land “in the box” opposed to “perfect on target” Step 2: Reduce Variability in the Process Taguchi: Even Small Deviations are Quality Losses

Step 3: Accommodate Residual Variability Through Robust Design A product/process that produces consistent, high-level performance "despite being subjected to a wide range of changing client and manufacturing conditions.

Cause and Effect Diagram (Ishikawa Diagram) Materials Machines Specifications / information People Vise position set incorrectly Machine tool coordinates set incorrectly Vice position shifted during production Part clamping surfaces corrupted Part incorrectly positioned in clamp Clamping force too high or too low Cutting tool worn Dimensions incorrectly specified in drawing Dimension incorrectly coded In machine tool program Material too soft Extrusion stock undersized Extrusion die undersized Extrusion rate too high Extrusion temperature too high Error in measuring height Steer support height deviates from specification

Exercise In your group, select a problem: äAt Muhlenberg äAnother organization Develop a cause and effect diagram to address the problem Deliverable: Develop the diagram and share solution with class

Zero Inventories Zero Defects Flexibility / Zero set-ups Zero breakdowns Zero handling / non value added Just-in-time Production Kanban Classical Push “Real” Just-in-time Mixed Production Set-up reduction Autonomation Competence and Training Continuous Improvement Quality at the source OrganizationMethodsPrinciples The System of Lean Production (Toyota, Citroen, …)

Avoid unnecessary inventory To be seen more as an ideal Two types of (bad) inventory: a. resulting from defects / rework b. absence of a smooth process flow Remember the other costs of inventory (capital, flow time) Pictures: Citroen Inventory in process Buffer argument: “Increase inventory” Toyota argument: “Decrease inventory” Principles of Lean Production: Zero Inventory and Zero Defects

Flexible machines with short set-ups Allows production in small lots Real time with demand Large variety Maximize uptime Without inventory, any breakdown will put production to an end preventive maintenance Avoid Non-value-added activities, specifically rework and set-ups Principles of Lean Production: Zero Set-ups, Zero NVA and Zero Breakdowns

Push: make to forecastPull: Synchronized production Pull: Kanban Visual way to implement a pull system Amount of WIP is determined by number of cards Kanban = Sign board Work needs to be authorized by demand Classical MRP way Based on forecasts Push, not pull Still applicable for low cost parts Part produced for specific order (at supplier) shipped right to assembly real-time synchronization for large parts (seat) inspected at source Methods of Lean Production: Just-in-time

Cycle Inventory Cycle Inventory Cycle Inventory Cycle Inventory Production with large batches End of Month Beginning of Month Cycle Production with large batches End of Month Beginning of Month Cycle Production with large batches End of Month Beginning of Month Cycle Production with large batches End of Month Beginning of Month Inventory End of Month Beginning of Month Produce Sedan Produce Station wagon End of Month Beginning of Month Produce Sedan Produce Station wagon End of Month Beginning of Month Produce Sedan Produce Station wagon End of Month Beginning of Month Methods of Lean Production: Mixed Production and Set-up reduction

Create local decision making rather than pure focus on execution Use machines / tools, but avoid the lights-off factory Automation with a human touch Cross training of workers Develop problem solving skills Organization of Lean Production: Autonomation and Training

Solve the problems where they occur - this is where the knowledge is - this is the cheapest place Traditional: inspect and rework at the end of the process Once problem is detected, send alarm and potentially stop the production Own ProcessNext ProcessEnd of LineFinal Inspection End User $$$$$ Rework Reschedule very minor minor delay Significant Rework Delayed delivery Overhead Warranty cost recalls reputation overhead Defect found Defect fixed Organization of Lean Production: Continuous Improvement and Quality-at-the- source

External Failure Costs Appraisal Costs Prevention Costs Internal Failure Costs Costs of Quality Costs of Quality