1
Q
Process “Plan Quality Management”
A
- Goal: identify quality requirements and/or standards for the project and its deliverables, and document how the project will demonstrate compliance.
- Inputs: project charter, project mgmt plan (req mgmt plan, risk mgmt plan, stakeholder engagement plan), project documents (assumpt log, req documentation, RTM, risk reg, stakeholder reg), EEFs, OPAs
- Tools+Techniques: Expert judgment, data gathering (benchmarking, brainstorming, interviews), data analysis (cost-benefit-analysis, COQ), multi criteria decision analysis, data representation (flowcharts, logical data model, matrix diagrams, mind mapping), test and inspection planning, meetings
- Outputs: Quality mgmt plan, quality metrics, PMPlan updates (Risk mgmt plan, scope baseline), Project documents updates (lessons learned reg, RTM, risk reg, stakeholder reg)
2
Q
Process “Manage Quality”
A
- Goal: translate the quality mgmt plan into executable quality activities that incorporate the org’s quality policies into the project
- Inputs: Quality mgmt plan, Project documents (lessons learned reg, quality control measurements, quality metrics, risk report), OPAs
- Tools+Techniques: data gathering (checklists), data analysis (alt., document, process and root cause analysis), multicriteria decision analysis, data representation (affinity, cause-and-effect, matrix and scatter diagrams; flowcharts,; histograms), audit, design for X, problem solving, quality improvement methods
- Outputs: quality reports, test and evaluation docs, CRs, PMPlan updates (quality mgmt plan; scope, schedule and cost baseline), project updates (issue log, lessons learned reg, risk reg)
3
Q
Process “Control Quality”
A
- Goal: verify that project deliverables and work meet the requirements specified by key stakeholders for final acceptance
- Inputs: Quality mgmt plan, Project documents (lessons learned reg, quality metrics, test and evaluations docs), approved CRs, deliverables, work performance data, EEFs, OPAs
- Tools+Techniques: data gathering (checklists, check sheets, statistical sampling, questionnaires and surveys), data analysis (performance reviews, root cause analysis), inspection, testing/product evaluat., data representation (cause-and-effect diagrams, control charts, histograms, scatter diagrams), meetings
- Outputs: Quality controls measurements, verified deliverables, work performance information, CRs, Updates to Quality mgmt plan, Project documents updates (issue log, lessons learned reg, risk reg, test and evaluat. docs)
4
Q
Quality vs. grade
A
- quality: degree to which a set of inherent characteristics fulfill requirements
- grade: a category assigned to deliverables having the same functional use but different technical characteristics
- Low-grade may not be a problem and may be acceptable, while low-quality is always a problem and never acceptable.
5
Q
Attribute sampling vs. variable sampling
A
- attribute sampling: the result either conforms or does not conform
- variable sampling: the result is rated on a continuous scale that measure the degree of conformity
6
Q
Cost of quality (COQ)
A
- Includes all costs incurred over the life of the product by investment in preventing nonconformance to requirements, appraising the product for conformance to requirements, and failing to meet requirements.
- In short: includes prevention costs (training, processes, time, etc.), appraisal costs (measuring, auditing, testing, etc.) and failure costs (internal - rework, scrap/ external - warranty, lost business, liabilities)
- cost of conformance: cost to avoid failure (prevention + appraisal)
- cost of nonconformance: cost because of failures
7
Q
SIPOC
A
- type of flowchart
- summarizes the inputs and outputs of one or more processes in table form and stands for Supplies, Inputs, Process, Outputs and Customers
- is used in the process “Plan Quality Management”
8
Q
Audit
A
- structured, independent process used to determine if project activities comply with organizational and project policies, processes and procedures
- objectives: identify good practices being implemented; identify nonconformities, gaps and shortcomings; share good practices from similar projects; offer assistance to improve the implementation of processes; highlight contributions of each audit in the lessons learned repository of the organization
9
Q
Design for X (DfX)
A
A set of technical guidelines that may be applied during the design of a product for the optimization of a specific aspect of the design. The X in DfX can be different aspects of product development, such as reliability, deployment, assembly, manufacturing, cost, service, usability, safety, and quality.
-> only used in ‘Manage Quality’
10
Q
mutual exclusivity
A
a statistical term describing two or more events that cannot coincide/occur at the same time. E.g. You cannot roll both a five and a three simultaneously on a single die.
11
Q
Design of Experiments (DOE)
A
- technique that can be used to analyze alternatives e.g. can be used look for ways to deliver the same level of quality for less cost
- fast and accurate technique that allows you to systematically change the important factors in a process and see which combinations have an optimal impact on the project deliverables
12
Q
Common vs special causes
A
- Common causes are normal, expected variances that occur. They are predictable and are not considered unusual. On a control chart, common causes of variance would be indicated by the random points within the control limits. (also known as “random” causes)
- special causes of variance are those causes that are not predictable or inherent in a system. They are usually related to some type of defect. On a control chart, special causes are represented by points beyond the control limits or as non-random points within the control limits. (also known as “assignable” causes)
13
Q
Accuracy vs. precision
A
- precision: less scatter, consistent, predictable
- accuracy: closeness to the target
-> high precision and low accuracy means the process should be adjusted
