Quality Management

Plan Quality Management: Tools - Data Representation - Flowcharts

Diagrams that show how various elements of a system relate to each other

Mutually Exclusive

Events that cannot occur at the same time.

cause and effect diagram

(Ishikawa Diagram) A decomposition technique that helps trace an undesirable effect back to its root cause.

Continuous Improvement

(kaizen) the implementation of a large number of small, incremental improvements in all areas of the organization on an ongoing basis

Manage Quality - Tools: Data Analysis

*Alternatives Analysis which evaluates the various options identified by the team. The goal is to determine the option that is best suited for the project environment. Document Analysis focuses attention on the documents that hold critical quality performance information, such as test reports, failure or defect reports, and variance reports. Members of the team review these documents to determine those processes that may not be in control. Document analysis helps the team shine a bright light on at-risk processes - those that may produce less-than-acceptable quality results. *Process Analysis follows the steps to identify areas that need improvement, based on data analysis of cycle times, queue sizes and limits, productivity, and waste. It involves a careful review of the quality process to ensure that it is working efficiently and effectively. The team researches quality tasks to make sure they add value to the project. Process analysis includes a review of the problems experienced and constraints encountered. *Root Cause Analysis or R-C-A. True to the name, use this technique to uncover the root-cause that leads to a problem, variance, defect, bug or risk. Picture the defect as a yellow leaf at the tip of a branch on a tree. With R-C-A, you trace that defect down through the branches, through the base of the tree, all the way back to the root. It takes some work, but once you've identified and removed the root cause, that defect or problem goes away.

Control Quality - Tools: Data Gathering

*Checklists are the first. A checklist defines the steps that we need to take to ensure the proper quality management actions have taken place. Checklists bring structure and completeness to our activities. *Check Sheets. A tally sheet or check sheet helps the team member collect useful data while performing an inspection or some other means of verifying quality. Think about the last time you took your car to the shop for an oil change. It's standard practice for that mechanic to inspect many areas of your vehicle while changing the oil. When the service technician hands you the keys, you'll get a check sheet along with the bill. That sheet shows the results of various inspections... the condition of tires, battery, brakes, wiper blades, air filters... the list goes on and on. The check sheet ensures that the shop inspects your car from top to bottom... and doesn't miss an opportunity to provide you with additional services! *Statistical Sampling is another powerful technique of Data Gathering. Most organizations that are performing quality control use statistical sampling rather than looking at each and every output. Sampling is much more practical and cost efficient. *Questionnaires and Surveys. For quality purposes, you may think of these questionnaires and surveys as happening after the fact. You've delivered the product to the customer, and now you are using this approach to gauge customer satisfaction. Defects or quality issues identified at this point are considered external failure costs because they are in the hands of the customer. You may hear these called "escaped defects!" Unfortunately, those defects can have significant cost implications

Control Quality - Inputs: Project Documents

*Lessons Learned Register for ways to improve these quality control activities. *Quality Metrics describe an attribute or feature and how it will be measured. The team develops these quality metrics while performing quality planning. Now, in this process, the team uses these metrics as a measurement to determine if they've met quality specifications. So, these metrics are vital! *Test and Evaluation Documents in the prior process of Manage Quality. These represent our testing plans that help determine if we've achieved quality objectives. Quality checklists are an example of these documents. In Control Quality, the checklists can be used to determine if the product conforms to quality standards. For instance, there might be 10 steps that should be followed prior to applying a final coat of paint to our product. If there are problems with the appearance of the final coat, the project team might go back and review the checklists... are they being followed? Are we missing a step?

Plan Quality Management: Tools - Data Representation - SIPOC

A diagram that defines the boundaries of a process and shows how its Suppliers, Inputs, Processes, Outputs, and Customers affect process quality. A flowchart or process map is a diagram of the inputs, actions, and outputs of procedures in a system. A flowchart helps you analyze how quality problems might occur. Flowcharts come in all shapes and sizes, but have some common elements. Process maps or flowcharts show the relationship of activities, branching, decision points, and the order of processing. There are many varieties of flowcharts, and one common example is the S-I-P-O-C model. SIPOC. stands for Suppliers, Inputs, Processes, Outputs, and Customers. SIPOC traces back to the Total Quality Management program and is a process improvement tool used in Lean manufacturing and Six Sigma. You can see how this type of flowchart would be useful in planning for quality, identifying potential quality issues, and understanding the total cost of quality. It's interesting to note that some practitioners reverse the order of the SIPOC model to emphasize the needs of the Customer. That model is called COPIS ...it starts with the Customer and works back to the Supplier. When the team uses flowcharts to represent steps in a process, flowcharts may be referred to as process flows or process flow diagrams. Again, the team can use these process flows to identify bottlenecks and defect-prone areas. These flowcharts help facilitate process improvement and planning for quality activities.

Histogram

A graph of vertical bars representing the frequency distribution of a set of data. (Pareto Chart)

Affinity Diagrams

A graphic tool used to organize and prioritize ideas after a brainstorming session

Design for Excellence (DFX)

A knowledge-based approach that attempts to design products that maximize all desirable characteristics A design process that ensures the outcome is manufacturable, maintainable, cost effective, and high quality. DfC -cost DfA-assembly DfA-manufacturing Dfl-logistics DfS-serviceability Key stakeholders must decide which attributes of a product are most important. Design decisions are made based on these rankings. Where the team should focus design efforts.

Total Quality Management

A philosophy that involves everyone in an organization in a continual effort to improve quality and achieve customer satisfaction.

Manage Quality - Tools: Quality Audits

A structured, independent process to determine if project activities comply with organizational and project policies, processes, and procedures. "Is the team following the quality plan?" "Do we comply with our quality policy?" "What process gaps can be identified?" "What best practices are the team following?" "What other best practices should the team implement?" "Have we captured this information in a lessons learned repository for the organization to use?" Goal = increase product acceptance and decrease the overall cost of quality

Plan Quality Management: Tools - Data Representation - Matrix Diagram

A table or chart that shows the strength of relationships between items or sets of items.

All of the following are tools used in Control Quality EXCEPT: A. Benchmarking B. Pareto charts C. Histograms D. Statistical sampling

A. This one is tricky because all of these tools are used in quality management! 'B', 'C', and 'D' are all used in Control Quality, but 'A' is used only in Plan Quality Management. Benchmarking is used to establish quality standards based on the quality attributes of other projects. Keep in mind that a Pareto Diagram is a type of Histogram.

Manage Quality - Tools: Data Representation

Affinity Diagrams. We talked about this concept in the Collect Requirements process of Scope Management. Recall that the word "Affinity" indicates a connection, a relationship, or a similarity. In this process, the team may use an affinity diagram to organize potential causes of defects or quality issues into groups. The team can determine which affinity group to focus on first, and take action from there. Cause-and-Effect Diagrams are used to identify factors that could lead to quality problems. This diagram is known as the flowchart with 4 names: 'Cause-and-Effect Diagram', 'Ishikawa Diagram', 'Why-Why Diagram', and 'Fishbone Diagram'. The second name is attributed to Kaoru Ishikawa, who is credited with this concept. That last name describes what these diagrams often look like - fish bones. If you hear discussion about a "Root Cause Diagram," then associate that as yet another name of a Cause and Effect Diagram! Flowcharts are the third technique for Data Representation. We covered flowcharts in detail in the prior process of Plan Quality Management. Flowcharts show a series of steps or actions that may lead to a quality problem or defect. Histograms are the next technique. A histogram is a vertical bar chart - a graphical representation of the distribution of data. A project manager might use a histogram to isolate the most common cause of quality problems. The Pareto diagram or chart is a histogram that's sorted in descending order, and can be used to identify and evaluate the greatest contributors to defects or their causes. Put simply, the Pareto is a ranked histogram Matrix Diagrams are 5th on the list. There are various shapes and formats for these matrix diagrams. Regardless of the form of the matrix, the purpose of the matrix diagram or chart is to display the strength of relationships between factors, causes, and objectives. Scatter Diagrams are a particularly powerful tool for spotting trends in data. Consider the following three scatter diagrams. Scatter diagrams are made using a dependent and independent variable. What you're looking for is correlation - some relationship that links the 2 variables.

Just In Time

An inventory-management approach in which supplies arrive just when needed for production or resale

Control Quality - Outputs: Control Measurements

Back in our discussion of Manage Quality, we talked about these quality control measurements as an input to that process. These are measurements of quality levels and compliance to standards or goals that were set. We said that you could think of these "Q-C" measurements as part of a feedback loop. The measurements are an output of Control Quality, and then they feed back into Manage Quality for evaluation.

On a control chart, the customer's acceptable quality limits are represented as: A. Control limits B. Mean C. Specification D. Normal distribution

C. The quality specification is the customer's quality requirements. 'A' represents the limits for what is in and out of statistical control, typically set at three standard deviations from the mean. 'B' is the average of all of the data points. 'D' is a statistical term relating to the way the data points are scattered.

Plan Quality Management - Tools: Data Analysis

Cost benefit analysis: How much will it cost to achieve this level of quality?" And, "What are the benefits?" The golden rule in quality is that all benefits of quality activities must outweigh the costs. The project team should perform analysis to understand these tradeoffs to make an informed decision. Potential benefits from meeting quality requirements include satisfied customers, less rework, higher productivity, and lower total costs. Measure the costs. Determine the benefits. See if the benefits exceed the costs and make the quality effort a worthwhile investment. Cost of Quality: Cost of Quality looks at the total costs incurred in order to reach quality goals. These costs include the investment to satisfy the quality requirements, the cost of inspecting or appraising results, and the price of rework - not hitting the targets. Failure costs, such as rework, scrap, dissatisfied customers, and other costs of low quality are known as "cost of poor quality" and may be abbreviated as C-O-P-Q.

Manage Quality helps to do all of the following except: A. Confirm that processes are used and meet objectives B. Improve efficiency and effectiveness of processes C. Analyze failures for quality improvement D. Discover defects to help meet specifications

D. All of the tasks listed except Answer-D deal with the process of quality, while -D is handling defects in the product from Control Quality.

Control Quality - Tools: Inspection

Here in Control Quality, you are inspecting the final product. So, one way to think of the difference is that in Validate Scope, you ask the question "Did we build the right thing?" In Control Quality, you ask the question "Did we build the thing right?" We're inspecting the deliverable to make sure we built it to the level of quality or specifications that we said we would. Validate Scope is about completeness. Control Quality is about correctness. The second distinction has to do with audits. Earlier, we talked about the tool of audits in the process of Manage Quality. So now, let's draw the line between audits and inspection: Audits focus on a plan or a process. The question is "Are we following the quality plan?" While Inspections focus on the final product. "Did we build the product correctly? Does it match the requirements and specifications?"

Quality Management Plan

In project planning, a document that contains strategies for meeting quality requirements for both the deliverable(s) and the project itself common elements found in a quality management plan: The quality objectives for the project, Quality-related activities planned for the team, Roles and responsibilities for those activities, Tools to be used, Deliverables and steps that will be covered by a quality review, The process and procedures for managing nonconformance, continuous improvement, and corrective actions.

Scatter Diagrams

Provide a visual way to examine possible relationships between two variables

Quality Improvement Methods

Plan do check act Six Sigma

Precision vs accuracy

Precision means that the values of repeated measurements are extremely close to each other - there's very little scatter. The results are clustered. Accuracy means that the measured value is very close to the true or intended value. To understand this difference, think of the steps that a marksman takes to adjust the sites of a new rifle. If the marksman is highly skilled, then it's likely that his first few shots will be tightly clustered, even if they are not hitting the center of the target. In quality terms, the results indicate precision - there's very little scatter. But, the early results may not exhibit accuracy - he's not hitting the bulls-eye - the intended target. The marksman makes small adjustments to the sites of the new rifle. Then, future results are both precise and accurate.

Quality Management

Processes: -Plan Quality Management (Planning): Quality Management Plan, Quality Metrics -Manage Quality (Executing): Change requests, test and evaluation docs -Control Quality (Monitoring and Controlling): quality control measurements, verified deliverables

Control Quality - Inputs: Deliverables

The deliverables are tested, measured, and inspected to ensure that they conform to quality standards.

Management Responsibility

The establishment and maintenance of a system of internal control is the responsibility of management

Manage Quality - Tool: Quality Improvement Methods

Quality Improvement Methods is listed as the 8th and final tool of Manage Quality. The use of many of the prior tools will uncover opportunities for quality improvement. For example, problem-solving, audits, and root-cause analysis all may lead to fresh perspectives and ideas. There are many methods for analyzing, evaluating, and improving quality processes. Two common models are Plan-Do-Check-Act made popular by Edwards Deming and Six Sigma introduced by Bill Smith at Motorola.

Prevention vs. Inspection

Quality is planned, designed, and built in—not inspected in.

Manage Quality - Outputs: Test and Evaluation Documents

Remember that Manage Quality is all about transforming the quality management plan into tasks that help the team achieve quality objectives for the project. This output embodies the spirit of the process. Test and evaluation documents may include checklists and references to the requirements traceability matrix. These documents become important inputs into the next process of Control Quality. We'll use the test and evaluation documents to evaluate our success or failure in achieving quality goals.

ISO 9000

Set of international standards on quality management and quality assurance, critical to international business

Special Causes vs Common Causes

Statistical process control Special - unusual and preventable by process improvement Common - normal, accepted

Statistical Independence

The absence of an association or covariation between two variables

Quality

The degree to which a set of inherent characteristics fulfills requirements.

Plan Quality Management

The process of identifying quality requirements and/or standards for the project and its deliverables, and documenting how the project will demonstrate compliance with quality requirements. (Planning) Inputs: Project Charter, PM Plan (requirements, risk, stakeholder, scope), project documents, EEFs, OPAs Tools: Expert Judgement, *Data Gathering (benchmarking, brainstorming, interviews), *Data analysis (CoQ, CoPQ), Decision making, *Data representation (Flowcharts, Logical data model, Matrix diagrams), *Test and inspection planning Outputs: *Quality Management Plan, *Quality metrics, PM Plan updates, Project doc updates

Control Quality

The process of monitoring and recording results of executing the quality activities to assess performance and recommend necessary changes. (Monitoring and Controlling) Inputs: Project management plan, *Project docs, approved change requests, *Deliverables, work performance data, EEFs, OPAs Tools: *Data gathering, data analysis, *Inspection, Testing/product evaluations, *Data representation, Control charts, meetings Outputs: *Quality control measurements, *Verified Deliverables, work performance information, change requests, project management plan updates, project documents updates Manage Quality is carried out during planning and executing phases. Manage Quality gives the Customer confidence that their requirements will be met. In contrast, Control Quality is carried out during executing and closing phases, and it demonstrates that acceptance criteria have been met. Manage Quality ensures that we do what we said we would do. Control Quality ensures that project outputs do what they were intended to do. Manage Quality is all about the process. Control Quality is all about the product.

Manage Quality

The process of translating the quality management plan into executable quality activities that incorporate the organization's quality policies into the project. (Executing) Purpose: 1. put quality management plan into practice 2. improve process Inputs: PM Plan, Project docs, OPAs, Tools: Data gathering, *Data analysis (alternatives, process, root cause) , Decision making, Data representation (Affinity diagrams, Cause and effect diagrams, flowcharts, histograms, matrix diagrams, scatter diagrams), Audits, Design for X, Problem solving, Quality Improvement Methods Outputs: *Quality reports, *Test and evaluation documents, change requests, project management plan updates, project doc updates Manage Quality uses the key tool of Audits to determine if the quality process is being followed. And, if it's adding value. Control Quality uses the key tool of Inspection to determine if the final product is acceptable. Does it match the requirements and specifications?

Plan Quality Management - Outputs: Quality Metrics

These measurements describe an attribute and how the Control Quality process will verify compliance for that trait. Quality Metrics define how quality will be measured in very specific terms. We're looking for a measurable attribute here - a value that we can determine and compare with what is required. For example, if we are controlling quality for a bottling plant, we might establish a quality metric that states each bottle coming off the line should be filled with exactly 500 milliliters of pure water.

Manage Quality - Outputs: Quality Reports

These reports provide summary and detailed information. At a high level, quality reports communicate the summary of findings and overall performance in meeting quality targets for the project. At a low level, quality reports present more tactical, detailed data, such as: All quality issues that have been escalated by the team, Proposals for improvements, and Recommendations for corrective action which could include rework and defects to fix.

Standard Deviation

a measure of variability that describes an average distance of every score from the mean

Six Sigma

a rigorous statistical analysis process that reduces defects in manufacturing and service-related processes 1 sigma = 317,500/1,000,000 defects 3 sigma = 2,700/1,000,000 defects 6 sigma = 3.4/1,000,000 defects 2 key points: First, Six Sigma is a quality management philosophy that sets very high standards for quality. Second, following the Six Sigma philosophy, 1 sigma quality represents a relatively low level of quality, 3 sigma quality is higher, and 6 sigma quality is even higher, describing a process that allows only 3.4 defects per 1,000,000.

attribute sampling vs. variables sampling

attribute sampling - the result either conforms or does not conform. variable sampling - result is rated on a continuous scale that measures degree of conformity

Control Quality - Tools: Data Representation

cause and effect, histogram, scatter *Control Charts: determine whether a process is in control - to see if it's stable and has predictable performance graphic presentations of process data over time, with predetermined control limits rule of 7: if 7 or more data points fall on one side of the mean, they should be investigated Remember, control charts help determine whether a process is in control. And, the process is considered out of control in 3 cases: 1. if a data point falls outside a control limit. 2. if seven consecutive data points fall below the mean. 3.if seven consecutive data points are above the mean.

Control Quality - Tools: Test and Product evaluation

ex) for software products May include: -stress testing -unit testing -usability testing -regression testing -integration testing

Customer Satisfaction

the extent to which a product's perceived performance matches a buyer's expectations

Control Quality - Outputs: Verified Deliverables

the goal of the entire quality effort. You follow the company's quality policy, establish standards of excellence for your project, work to attain these levels, and then receive verification...your deliverables pass inspection. They are acceptable. That's what it's all about! It's important to note that these Verified Deliverables become an input to the Validate Scope process for formalized acceptance from the customer or sponsor. Verified Deliverables are a strong connection point from the Quality Management knowledge area back into Scope Management.

tolerances vs control limits

tolerances - specified range of acceptable results. Is product acceptable? control limits - identify boundaries of common variation. Is process acceptable?