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Chapter 2. Principles of Six Sigma. Six Sigma Green Belt Body of Knowledge. Six Sigma encompasses a vast collection of concepts, tools, and techniques that are drawn from many areas of business, statistics, engineering, and practical experience .
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Chapter 2 Principles of Six Sigma
Six Sigma Green Belt Body of Knowledge • Six Sigma encompasses a vast collection of concepts, tools, and techniques that are drawn from many areas of business, statistics, engineering, and practical experience. • Many of these subjects are technical; others deal with management and organizational issues. • Practitioners need a balanced set of both the “hard” and the “soft” disciplines in order to apply and implement Six Sigma effectively. • [See Table 2.1]
Six Sigma Projects and Organizational Goals • Six Sigma projects are driven by needs and opportunities to achieve an organization’s strategic goals, objectives, and action plans. • Many organizations use “dashboards” and “balanced scorecards” to track key measurements at the operational and strategic levels, respectively.
Balanced Scorecard • Financial perspective • profitability, revenue growth, return on investment, economic value added (EVA), and shareholder value • Internal perspective • quality levels, productivity, cycle time, and cost. • Customer perspective • service levels, satisfaction ratings, and repeat business • Innovation and learning perspective • intellectual assets, employee satisfaction, market innovation, and skills development 4
Problem Classification Six Sigma Lean tools Creative thinking Special tools Combined approaches • Conformance problems are defined by unsatisfactory performance that causes customer dissatisfaction. • Efficiency problems result from unsatisfactory performance from the standpoint of stakeholders other than customers. • Unstructured performance problems result from unsatisfactory performance in processes that are not well-specified or understood. • Product design problems involve designing new products or redesigning existing products to better satisfy customer needs. • Process design problems involve designing new processes or substantially revising existing processes. 5
Six Sigma in Services All Six Sigma projects have three key characteristics: a problem to be solved, a process in which the problem exists, and one or more measures that quantify the gap to be closed and can be used to monitor progress.
Key Performance Measures in Services • Accuracy • Cycle time • Cost • Customer satisfaction
Process Concepts • Process owners - individuals or groupswho are accountable for process performance and have the authority to control and improve their process. • Stakeholders – who are or might be affected by an organization’s actions and success: customers, the workforce, partners, collaborators, governing boards, stockholders, donors, suppliers, taxpayers, regulatory bodies, policy makers, funders, and local and professional communities.
Types of Processes • Value-creation processes – those most important to “running the business” • Design processes – activities that develop functional product specifications • Production/delivery processes – those that create or deliver products • Support processes – those most important to an organization’s value creation processes, employees, and daily operations
Process Requirements • Value creation process requirements usually depend on consumer or external customer needs. • Support process requirements are driven by internal customer needs and must be aligned with the needs of key value-creation processes
Process Variation Measurement Instruments Operators Methods Materials INPUTS PROCESS OUTPUTS Tools Human Inspection Performance Machines Environment 12
Types of Process Variation • Common causes - random variation that cannot be identified or explained. However, their combined effect is stable and can usually be predicted statistically. • A system governed only by common causes is called a stable system. • Special (assignable) causes – external sources of variation not inherent in a process.
Problems Created by Variation • Variation increases unpredictability. • Variation reduces capacity utilization. • Variation contributes to a “bullwhip” effect. • Variation makes it difficult to find root causes. • Variation makes it difficult to detect potential problems early. 14
Lessons Learned • Quality is made at the top. • Rigid procedures are not enough. • People are not always the main source of variability. • Numerical goals are often meaningless. • Inspection is expensive and does not improve quality. 20
Deming’s Funnel Experiment • Rule 1: Leave the funnel alone • Rule 2. Measure the deviation from the point at which the marble comes to rest and the target. Move the funnel an equal distance in the opposite direction from its current position. • Rule 3. Measure the deviation from the point at which the marble comes to rest and the target. Set the funnel an equal distance in the opposite direction of the error from the target. • Rule 4. Place the funnel over the spot where the marble last came to rest.
Six-Sigma Metrics • Metric– a verifiable measurement stated numerically or in qualitative terms • Measurement – the act of quantifying the performance dimensions of products, services, processes, and other business activities. • Measures and indicators – the numerical information that results from measurement
Types of Metrics • Discrete metric – one that is countable. • In quality control terminology, a performance characteristic that is either present or absent in the product or service under consideration is called an attribute, and such data are referred to as attributes data. • Continuous metric – one concerned with the degree of conformance to specifications. • In quality control, continuous performance characteristics are often called variables, and such data are referred to as variables data.
Six-Sigma Metrics • Nonconformance (defect or error) – any mistake or error that is passed on to a customer • Unit of work – output of a process or process step • Nonconforming unit of work – one that has one or more nonconformances
Six-Sigma Metrics • Defects per million opportunities (dpmo) = Number of defects discovered opportunities for error 1,000,000 (2.3) A six-sigma quality level represents a dpmo of 3.4
Statistical Basis for Six Sigma • Ensuring that process variation is half the design tolerance while allowing the mean to shift as much as 1.5 standard deviations in either direction, resulting in at most 3.4 dpmo either above or below the tolerance limits.
Sigma Level Calculations • A k-sigma quality level satisfies the equation: k*process standard deviation = tolerance/2 (2.4) • Excel formula for sigma level: =NORMSINV(1 – dpmo/1000000) + SHIFT
Six Sigma Terminology Although originally developed for manufacturing in the context of tolerance-based specifications, the Six Sigma concept has been operationalized to any process and has come to signify a generic quality level of at most 3.4 defects per million opportunities.
Additional Six Sigma Metrics • Throughput yield • Rolled throughput yield (RTY) – the proportion of conforming units that results from a series of process steps.
Problem Solving Process • Redefining and analyzing the problem • Generating ideas • Evaluating and selecting ideas • Implementing ideas
DMAIC Methodology • Define • Measure • Analyze • Improve • Control
Define • Describe the problem in operational terms • Drill down to a specific problem statement (project scoping) • Identify customers and CTQs, performance metrics, and cost/revenue implications
Measure • Understand causal relationships between process performance and customer value. Y = f(X) where Y = customer CTQs and X represents critical input variables that influence Y
Data Collection Issues • What questions are we trying to answer? • What type of data will we need to answer the question? • Where can we find the data? • Who can provide the data? • How can we collect the data with minimum effort and with minimum chance of error?
Analyze • Focus on why defects, errors, or excessive variation occur • Experimentation and verification to verify Y = f(X) relationships
Improve • Improve the X variables so as to improve Y • Idea generation • Brainstorming • Evaluation and selection • Implementation planning
Control • Maintain improvements • Standard operating procedures • Training • Checklist or reviews • Statistical process control charts
Lean Six Sigma • …an integrated improvement approach to improve goods and services and operations efficiency by reducing defects variation, and waste. • Lean production addresses visible problems in processes, for example, inventory, material flow, and safety. • Six Sigma is more concerned with less visible problems, for example, variation in performance. 40
Lean Thinking • Lean thinking focus on the elimination of waste in all forms and smooth, efficient flow of materials and information throughout the value chain to obtain faster customer response, higher quality, and lower costs. • Value-added activities are those that add value to a product by transforming it. Non-value-added activities are those that do not add value, such as rework or waiting for tools or service. • Lean thinking considers nonvalue-added activities as waste
Types of Waste • Overproduction • Waiting time • Unnecessary transportation • Unnecessary processing • Inventory • Unnecessary motion • Production defects
Tools of Lean Production • The 5S’s: seiri(sort), seiton(set in order), seiso(shine), seiketsu(standardize), and shitsuke(sustain). • Visual controls. • Efficient layout and standardized work. • Pull production. • Single minute exchange of dies (SMED). • Total productive maintenance. • Source inspection. • Continuous improvement.
Theory of Constraints • Theory of Constraints (TOC) – a set of principles that focuses on increasing process throughput by maximizing the utilization of all bottleneck activities in a process. • A constraintis anything in an organization that prevents it from moving toward or achieving its goal. Constraints determine the throughput of a facility because they limit production output to their own capacity. • TOC focuses on identifying constraints, managing bottleneck and nonbottleneck work activities, linking them to the market to ensure an appropriate product mix, and scheduling nonbottleneck resources to enhance throughput.
