Manufacturing Training Seminars

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Quality Management for the Technology Sector 

Quality Management for the Technology Sector is a 9-class, 16-hour program of instruction addressing quality management in high-technology environments.  The program provides in-depth coverage of the quality technologies that work, and it contains numerous real world examples based on the instructor’s 35-year consulting and teaching career in the aerospace, electronics, transportation, and biomedical device industries.

Materials

• Quality Management for the Technology Sector, published by Butterworth-Heinemann.

Who Should Attend

Executives, managers, engineers, quality assurance specialists, supply chain management specialists, and others desiring an in-depth understanding of the technologies necessary for continuous improvement in high technology environments.

Quality Management for the Technology Sector Syllabus

• Class 1:  Introduction and the Continuous Improvement Concept.  The evolution of quality management approaches.  Contemporary quality management overview.  Corporate-wide quality assurance responsibilities.  Quality assurance definitions.   Navigating the three-letter-acronym jungle.  Building a continuous improvement management approach with staying power.  Why quality programs fail.  The nature and shortfalls of relying on inspection.  Designing for quality in products and processes.  Focusing on customer requirements and expectations.  Quantifying quality and charting a continuous improvement approach.  Prioritizing quality objectives.  Making quality permeate the organization.

• Class 2:  Quality Measurement Systems.  The nature of quality measurement.  Defining and quantifying current quality levels.  How to measure quality.  Capturing scrap, rework, and warranty quality data.  The cost of quality concept.  Developing aggressive, attainable, and measurable quality improvement objectives.  Pareto analysis.  Sorting quality by cost, defect count, and client impact.  Meaningful quality assurance visual displays.  Posting quality assurance metrics.  A recommended quality measurement system.  Case study:  Quality measurement system implementation challenges in a material handling equipment manufacturer.

• Class 3:  Root Cause Identification and Corrective Action.  The four-step problem solving process.  Brainstorming, fishbone diagrams, and fault tree analysis. Fault tree analysis advantages over other failure cause identification systems.  Objectively identifying all potential nonconformance causes.  Unearthing failure causes in complex systems.  Using failure mode assessment and assignment matrices.  Corrective action options and order of precedence.  Corrective action boards.  Nonconforming material management.  Using the material review function as a vehicle for forcing corrective action.  Evaluating corrective action efficacy.   Case study:  Laser optics debonding in a laser system manufacturer.

• Class 4:  Employee and Supplier Involvement.   Employee involvement and empowerment.  Tapping the organization’s most valuable resource.  Applying theories of motivation to individuals, teams, and the organization.  Developing listening skills.  Defining expectations.  Quality circles versus employee focus teams.  Providing the right tools to facilitate employee involvement.  The danger of slogans.  Suggestion programs.  Overcoming the fear of ceding authority.  Enlisting supplier support and developing suppliers as team members.  Developing sensible supplier requirements.  Approved supplier list developments.  Selecting and working with smaller numbers of higher quality suppliers.

• Class 5:  Industrial Statistics.  The nature of variability.  Statistics for non-statisticians, including basic statistical concepts and their applications to business, engineering, and manufacturing decisions.  Deterministic versus statistical thinking.   The normal curve and its meanings in manufacturing and engineering.  Excel’s statistical features.  Understanding, identifying, and reducing variability.   Sampling plans, inspection, and statistical process control.   Statistical process control implementation strategies.  Lot acceptance test considerations.   Case study:  Lot acceptance testing statistical inconsistency resolution in a  medical equipment manufacturer.

• Class 6:  Design of Experiments.  The experimental design approach and experimental design strategies.  Using analysis of variance to differentiate random versus statistically-significant causes.  Evaluating the effects and significance of multiple potential factors simultaneously.  Fractional factorial experiments.   Taguchi design of experiments approaches.   Selecting factors for evaluation.  Using Excel to simplify data reduction.  Financial, performance, and customer satisfaction advantages in identifying and controlling critical factors.  Case study:  Taguchi application in a filament wound pressure vessel manufacturer.

• Class 7:  Quality Function Deployment.  Quality function deployment overview.  Quality function deployment historical origins.  Deploying the voice of the customer.   Defining customer requirements and expectations.  Incorporating customer inputs in requirements definition.   Identifying approaches for satisfying each requirement.  Requirements conflicts and their resolution.   The WHAT, HOW, and HOW MUCH approach to quality function deployment.  Building the House of Quality.   Quality function deployment benchmarking. 

• Class 8:  Delivery Performance Improvement.   Developing and meeting production schedules.  The 6Ps of improved delivery performance.  Understanding and managing the nature of the relationship between capacity, lead time, and schedule.  The impacts of process robustness, production control, productivity, and procurement on delivery performance.   Organizing for on time production delivery.  Quick tools for identifying the source of schedule performance shortfalls.  Case study:  Correcting a severe behind schedule condition in a composite structures equipment manufacturer.

• Class 9:  Putting It All Together.  Recommended strategies for overall continuous improvement in the technology sector.  Integrating sales, marketing, engineering, manufacturing, supply chain management, and field services efforts.  Implementation risks and risk mitigation strategies.  A suggested continuous improvement roadmap.