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Data Analysis
Breaking down the data to draw significant insights. Steps involved in data analysis - validate (make sure that the data is good), summarize (compute central tendency and dispersion), assess (histograms, etc) search for structure (relationship between variables with scatter plots, correlation, regression, etc), compare (mean, standard deviation, etc) and present results and draw conclusions.

An event of nonconformance to specification. Occurrence is measured in DPU, DPO, DPMO or Sigma Level. A given unit may have any number of defects - based on the number of opportunities. An unit with one or more defects is defective. Defects are caused by errors and measured using c-chart or u-chart. A binomial distribution characterizes defectives.

Delphi Method
developed by N Dalkey & O Helmer (1953) in order to address military projects at the RAND Corporation. Since its creation, the method has been used frequently to make predictions, seek consensus and generate ideas. The technique recognizes human judgement as legitimate and useful input and allows experts to generate ideas systematically for a complex problem.

1 form the team
2 selection of experts - most studies use a 15-35 member panel
3 develop the first set of question or issues for idea generation
4 transmission of the first set of questions to experts
5 analysis of the first round of responses and feedback
6 preparation and transmission of the second set of questions
7 analysis of the second round of responses
8 resolution

Deming's 14 Points

1 Establish Constancy of Purpose: plan and manage to the plan; detect and correct deviations.
2 Improve constantly and forever every system of production and service: small continuous improvement is better than infrequent quantum leaps.
3 Eliminate numerical goals and quotas, including management by objective: unsupported arbitrary objectives can be both restrictive & demoralizing.
4 Eliminate fear so that everyone may work effectively for the Company: mistakes happen and fear of disclosure impedes correction.
5 Institute leadership: managers must not be cops or directors but rather coaches of the creative team.
6 End the practice of awarding business largely on the basis of price: product quality, product improvement and reliability of supply are important.
7 Break down the barriers between departments: encourage communication and cooperation - eliminate chimneys and silos.
8 Institute training on the job: as product and process content grows, not all employees come equally prepared.
9 Eliminate the annual rating or merit system: performance is subject to variation whereas shared reward develops teamwork.
10 Institute a vigorous program of education and self-improvement: as employees promote the company, the company must develop its employees.
11 Eliminate slogans and exhortations: management, not an individual worker, is responsible for system performance.
12 Cease dependence on mass inspection: it is impractical to sort quality into a system that produces bad product.
13 Adopt the new philosophy: every department of the company can quantitatively measure its output.
14 Create a structure in top management to accomplish the transformation: successful systems can only be introduced and maintained by top management.

Density Function
The function which yields the probability that a particular random variable takes on any one of its possible values.

Design Controls
Engineering calculations, methods, reviews, tests, tools, etc., to detect the potential failure modes prior to engineering release.

Design for Manufacturability and Assembly
A simultaneous engineering process designed to optimize the relationship between design function, manufacturability, cost, weight and ease of assembly.

Design Information Checklist
A mistake proofing checklist designed to assure that all important items were considered in establishing design requirements.

Design Reviews
A proactive process to prevent problems and misunderstandings. SAE paper - Reliability Problem Prevention Method for Automotive Components - Development of GD3 Activity and DRBFM (Design Review Based on Failure Mode).

Design Validation
Testing to ensure that product conforms to defined user needs and/or requirements. Design validation follows successful design verification and is normally performed on the final product under defined, operating conditions. Multiple validations may be performed if there are different intended uses.

Design Verification
Testing to ensure that all design outputs meet design input requirements. Design verification may include activities such as: Design Review, Performing Alternate Calculations, Understanding Tests & Demonstrations and Review of Design Stage Documents Before Release.

Detection vs. Prevention
Detection tolerates waste, prevention avoids waste.

Design Failure Mode and Effects Analysis.

Material defining the process to be followed (e.g, quality manual, operator instructions, graphics, pictorials).

Design of Experiments

The probability that an item will continue to function at customer expectation levels, at the useful life without requiring overhaul or rebuild due to wearout.

U V W X Y Z Acronyms
Food for Thought !
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