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 instructorís
35-year consulting and teaching career in the aerospace, electronics,
transportation, and biomedical device industries.
Management for the Technology Sector
will provide attendees with the ability to:
define the organizationís current quality status.
critical factors influencing product and process quality.
a continuous improvement roadmap with measurable and meaningful
and deploy contemporary improvement technologies, including
quality measurement, Pareto analyses, root cause identification
and corrective action systems, statistical and design of
experiments concepts, employee and supplier involvement, quality
function deployment, and delivery performance improvement.
include a technical or management background in a technology-based
case studies are utilized extensively in this program, and during
the program attendees are encouraged to share their experiences and
challenges with this group.
program is based on our book published by Butterworth-Heinemann.
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
Management for the Technology Sector Syllabus
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
quality objectives. Making
quality permeate the organization.
2: Quality Measurement
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
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
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.
4: Employee and Supplier
Employee involvement and empowerment.
Tapping the organizationís most valuable resource.
Applying theories of motivation to individuals, teams, and the
listening skills. Defining
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
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. Excelís 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.
6: Design of Experiments.
The experimental design approach and experimental design
strategies. Using analysis of variance to differentiate random versus
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.
7: Quality Function
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.
8: Delivery Performance
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
9: Putting It All
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.