Optimizing and controlling process through statistical process control Chapter 18 page 442 Doaa Abu Alwafa

STATISTICAL PROCESS CONTROL DEFINED All process are affected by multiple factors such as: 1.The environment the machines employed 2.The materials used 3.The methods(work instruction) provides 4.The measurement taken 5.The manpower(people) who operate the process These factors called the 5 M’s

STASTISTICAL PROCESS CONTROL DEFINED Statistical process control (SPC) is a statistical method of separating variation resulting from special causes from variation resulting from natural causes in order to eliminate the special causes and to establish and maintain consistency in the process, enabling process improvement.

Rational for SPC 1.Control of variation 2.Continual improvement 3.Predictability of processes 4.Elimination of waste 5.Product inspection

Control chart development Data categoryChart typeStatistical qualityapplication Variables(measured values) x bar-R( See figure page 453 Mean value and rangeCharts dimensions and their precision, weight, time, strength, and other measurable quantities. example: anything physically measurable x tilde-R(Median and rangeCharts measurable quantities, similar to x bar-R, but requires fewer calculation to plot. Example as above

Control chart development(continue) Data categoryChart typeStatistical qualityapplication Variables(measured values) x-Rs(also called x- chart See figure page 453 Individual measured values Used with long sample intervals; when subgrouping not possible. Example: products made in batches such as solution, coaching, etc. or grouping too expensive. Histogram must be normal

Control chart development(continue) Data categoryChart typeStatistical qualityapplication Attributes(counted values) p-chart See figures page 454, 455 Percentage defective (also fraction defective) Charts the number of defects in samples of varying size as a percentage or fraction. Example: anywhere defects can be counted np-chart(also pn)Number of defective pieces Charts the number of defective pieces in sample of fixed size. Example: as above, but in fixed- size samples

Control chart development(continue) Data categoryChart typeStatistical qualityapplication Attributes(counted values) c-chart See figure page 457 Number of defectsCharts the number of defects in a product( single piece) of fixed size. Example: specific assemblies or products( e.g., pc boards, tires) u-chartNumber of defects per unit area, time, length, etc. Charts the number of defects in a product of varying size (i.e., unlike products). Example: Carpet( area), extrusions length)

Management’s role in SPC 1.Commitment 2.Training 3.Involvement See page 462

Role of the total quality tools There are several tools: 1.Pareto charts 2.Cause and effect diagrams 3.Stratification 4.Check sheets 5.Histograms 6.Scatter diagrams 7.Run charts and control charts 8.Flow charts 9.Design of experiments 10.Five-s 11.Failure mode and effects analysis(FMEA)

Role of the total quality tools(continue) With SPC, the total quality tools have a dual role: First: they help eliminate special causes from the process so that the process can be brought under control. Second: their second role comes into play when, from time to time, the control chart reveals cause or when the operators wants to improve a process that is in control.

Implementation and deployment of SPC The implementation steps are divided into three phases: 1.preparation 2.planning 3.execution

Implementation and deployment of SPC (continue) phaseresponsibilityaction preparationTop management Consultant or in-house expert Step 1:Commit to SPC Step 2:Organize SPC committee Step 3:Train SPC committee planningSPC committee assisted by consultant or experts Consultant or in-house expert QA Management Step 4: Set SPC objectives Step 5:Identify target processes Step 6: train appropriate operators and support personnel Step 7: ensure repeatability of instruments and methods Step 8: delegate responsibility for operators to play key role

Implementation and deployment of SPC (continue) phaseresponsibilityaction executionSPC committee, operators, suppliers, customers Operator w/ expert assistance Consultant or in-house expert Operator Operator w/ expert assistance Operator SPC committee and management Operator w/ assistance as required All Step 9: flowchart the process Step 10: eliminate the special causes of variation Step 11: develop control charts Step 12: collect and plot SPC data; monitor Step 13: determine process capability Step 14: Respond to trends and out-of-limits data Step 15: track SPC data Step 16: eliminate root causes of any new special causes of variation Step 17: continually improve the process (narrow the limits)

Inhibitors of SPC 1.Capability in statistics 2.Misdirected responsibility for SPC 3.Failure to understand the target process 4.Failure to have processes under control 5.Inadequate training and discipline 6.Measurement repeatability and reproducibility 7. low production rates See page