Manufacturing - Summary

"A state of statistical control is not a natural state for manufacturing processes. It is instead an achievement, arrived at by elimination one by one, by determined effort, of special causes of excessive variation" - W. Edwards Deming
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Production Planning and Control

Process

Process Types

  • Assembly
  • Machining
  • Fabrication
  • Evaluation

Process Control Systems

Cost of Quality Model/Loss Function
Sequence Control
Certification Control
Variance Authorization
Rework/Repair Processing
Configuration Control
  • Vendor Lot ID
  • Fixtures
  • CNC Software
  • As-built

    Process Characteristics

    • Definition Method and Control
    • Equipment Cost of Ownership
      • Purchase Cost
      • Maintenance Cost
      • Supply Cost
      • Fixture Cost
      • Emission Cost
      • Operator Cost
      • Disposal Cost
    • Capability
    • Reliability
    • Flexibility
    • Ergonomics Issues
      • Increase Flexibility
      • Increase Productivity
      • Reduce Repetitive Motion Injuries
      • Improve Safety
    • Safety Priorities
      1. Reduce accident frequency
      2. Reduce proportion of accidents that result in injury
      3. Reduce lost days/injury
      Safety Techniques
      -Threshold Limit Values TLVs
      -procedures/training
      -warnings
      -protective gear
      -automation

    Maintenance Controls

    Corrective-response to failure
    Preventive-fixed interval/fixed ratio, wear-out replacement
    Predictive-adaptive

    Labor

    Attendance/Overtime
    Training/Certification
    Methods Analysis
  • Time Study Sampling and Prediction
  • Methods Improvement
  • Ergonomics

    Work Force Stability

    s=(2T)/(m*d)
    where:
    S = Stability Index
    T = Total length of service of all employees in years
    m = Number of individuals employed
    d = Difference in years between the average recruitment age and average retirement age

    S = 1 provides a good trade-off between hiring/training costs and risk of mass retirements

    Shift Scheduling

    Characteristics of 40-hour weekly schedule
    • Likely availability of management resources
    • Good access to engineering and support services
    • Ease of consistent communication with all employees
    • Poor utilization of equipment and inventory
    Characteristics of 24-hour by 7-day weekly schedule
    • Difficult to organize for full coverage with 40-hour shifts
    • Scarce management resources for late, weekend shifts
    • Poor access to engineering and support services for late, weekend shifts
    • Consistent communication with all employees difficult
    • Good utilization of equipment and inventory

    Methods Analysis

    • Time Study Sampling and Prediction
    • Methods Improvement

    Learning Curve

    Y(n)=Y(1)n^-b; where Y(n)=Time to produce nth unit, Y(1)=Time to produce 1st unit, b=Learning Rate Factor
    Factors that influence the value of b include:
    • process complexity
    • level of automation
    • process aids
    • worker experience

    Quality Control

    Sampling/Inspection

    data types
  • continuous numeric
  • discrete numeric
  • discrete attribute

    practical constraints

  • time
  • money
  • population preservation
  • accessibility

    Sample Type Characteristics
    Sample Type
    AdvantagesConvenienceJudgementRandom
    Little PlanningYYN
    QuickYYN
    EconomicalYYN
    Representative of populationNNY
    Statistical analysis validNNY

    Random sampling experimental controls

  • same instrument
  • same measurement technique
  • single, well-defined population
  • essentially same conditions

    Sample Size Characteristics
    Reliability
    Precision80%90%95%99%
    10%426897166
    5%165271385664
    1%41096676960416590
    Precision - how close is sample mean to population mean
    Reliability - how repeatable are the results
    AQL MIL-STD-105D

    Statistical Process Control

  • Assignable vs. Random Variation
  • Central Limit Theorem - parent population is IID Independent, Identically Distributed, then means of samples of size "n" will be normally distributed with same mean as parent population and predictably smaller std deviation

    out of control indicators

  • outliers
  • trends
  • oscillation
  • goal posting hugging
  • mean hugging
  • runs
  • AT&T Standards

    Capability

  • cp=(USL-LSL)/6s
  • cpu=(USL-xbar)/3s
  • cpl=(xbar-LSL)/3s
  • cpk=MIN(cpu,cpl)

    Pre Control

    Design of Experiments

  • factorial vs. fractional factorial
  • Evolutionary Operations (EVOP)
  • Taguchi Methods
    • Parameter Design
    • Loss Function
    • Linear Graph
    • Signal to Noise Ratio
    Additional References
    • Babcock, D.L. Managing Engineering and Technology, 2nd ed., Prentice Hall, Upper Saddle River, 1996.
    • Bedworth, D.D., Bailey, J.E., Integrated Production Control Systems: Management, Analysis, Design, Wiley, New York, 1982.
    • Bhote, K.R., World Class Quality: Design of Experiments made Easier, more Cost Effective than SPC, American Management Association, New York, 1988.
    • Box, G.E.R., Hunter, W.G., Hunter, J.S., Statistics for Experimenters, Wiley, New York, 1978.
    • Dhillon, B.S., Engineering Management: Concepts, Procedures and Models, Technomic, Lancaster, 1987.
    • Fukuda, R., Managerial Engineering: Techniques for Improving Quality and Productivity in the Workplace, Productivity, Inc., Stamford, 1983.
    • Glos, R.E, Steade, R.D., Lowry, J.R., Business: Its Nature and Environment - An Introduction, 8th ed., South-Western, Cincinnati, 1976.
    • Groover, M.P., Automation, Production Systems, and Computer-Aided Manufacturing, Technomic, Lancaster, 1987.
    • Konz, S.A., Work Design: Industrial Ergonomics, 2nd ed., Publishing Horizons, Columbus, 1987.
    • Orlicky, J., Material Requirements Planning: The New Way of Life in Production and Inventory Management, McGraw-Hill, New York, 1975.
    • Peterson, R., Silver, E.A., Decision Systems for Inventory Management and Production Planning, Wiley, New York, 1979.
    • Rosaler, R.C., Rice, J.O., Industrial Maintenance Reference Guide, McGraw-Hill, New York, 1987.
    • Taguchi, G., Introduction to Quality Engineering: Designing Quality into Products and Processes, Quality Resources, White Plains, 1989.

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