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The Management and Industrial Engineering Approaches to Lean Production
Published in Darina Lepadatu, Thomas Janoski, Framing and Managing Lean Organizations in the New Economy, 2020
Darina Lepadatu, Thomas Janoski
Lean management and Six Sigma are very similar in terms of methodology and implementation, and Japanese production processes have influenced approaches. However, they are different on three counts. First, lean management is more focused on eliminating waste, ensuring efficiency, and developing effective teams on the production floor. Six Sigma is much more oriented toward statistics in reducing defects and variability. Second, the main difference is that lean production focuses more on quality control techniques that are diffused throughout the organization through teamwork processes. Six sigma may have teams, but whether they reach the shop floor level is often in question. More recently, “Lean Six Sigma” has combined many lean production and Six Sigma ideas, and this represents lean manufacturing with flow and waste issues, and Six Sigma, with variation and design approaches. Companies such as GE, Ford, Accenture, Verizon, and IBM have used Lean Six Sigma to focus transformation efforts on efficiency and growth. And third, lean production is much more organizationally controlled by corporations and firms, while Six Sigma is a professionally oriented system with some of its organization outside the firm (i.e., ISO and ASQ). From our perspective, lean Six Sigma is different from lean production because of its much weaker teamwork approach on the shop floor.9
Safety Aspects, Failure Mode and Effect Analysis, and Safety Enhancement Technologies
Published in Siyong Kim, John Wong, Advanced and Emerging Technologies in Radiation Oncology Physics, 2018
Lean six sigma is an analysis process that combines the six sigma (6σ) philosophy with the lean approach. The concept of 6σ may not seem immediately applicable in the healthcare setting. The aim in industries that apply 6σ is that a process produces 99.99966% of items without error, which is clearly desirable in manufacturing electronic components, but the number of patients seen in radiation oncology and the clinical variability make this a difficult concept to apply. Hence, the analysis system of lean six sigma is to consider the stages a patient progresses through in isolation and analyze them for efficiency (waste). The lean six sigma concept can be implemented and analyzed by following the acronym DMAIC—define, measure, analyze, improve, and control. When a logistical problem within a department is discovered (e.g., the flow of brachytherapy patients on their treatment day), each of the points of DMAIC can be spelled out, a process map can be drawn up, and bottlenecks in the system should become obvious and can be rectified. An example of a lean six sigma for surgical wait times has been carried out for the Veterans Affairs system (Valsangkar et al., 2017).
Improvement Activities and Projects
Published in Ian Madden, Always Making Progress, 2022
Lean Six Sigma DMAIC is a structured problem-solving process where the project moves through each of the stages defined by DMAIC (Define, Measure, Analyse, Improve, Control). A ‘toll gate' review is held at the end of each stage. DMAIC projects are delivered by certified project managers called ‘belts.' To qualify for a belt, the Practitioner must attend training, pass an exam and submit a successful project to an external assessor to confirm they are able to apply their expertise effectively (Figure 7.8).
Problem framing: Essential to successful statistical engineering applications
Published in Quality Engineering, 2022
Roger W. Hoerl, Diego Kuonen, Thomas C. Redman
Good statistical engineering, quality improvement in general, and even statistics and data science processes acknowledge the importance of properly defining the problem. For example, the first two phases of the statistical engineering process, as detailed in the Statistical Engineering Handbook (Hare et al. 2021), published by the International Statistical Engineering Association (ISEA), are “Identify Problem” and “Provide Structure.” Similarly, the first step of the Lean Six Sigma DMAIC approach (“Define, Measure, Analyze, Improve, Control”) is “Define”; that is, define the problem (Snee and Hoerl 2018). Furthermore, the first step of the framework for data science recommended by the International Data Science in Schools Project (IDSSP Curriculum Team 2019) is called “Problem elicitation and formulation.”
Improving the service quality of telecommunication companies using online customer and employee review analysis
Published in Quality Management Journal, 2020
Akhouri Amitanand Sinha, Suchithra Rajendran, Roland Paul Nazareth, Wonjae Lee, Shoriat Ullah
Lean six-sigma is a widely used framework in various industries throughout the world (Alhuraish, Robledo, and Kobi 2017). Toyota production system led by Taiichi Ohno was the pioneers of the lean philosophy (Womack and Jones 1996). The ideology behind the lean system is to eliminate all mudas or waste from the system (Womack and Jones 1996). On the other hand, six-sigma was developed by Motorola in 1980s and popularized by General Electric in 1995 (Black and Revere 2006). It is a systematic technique to reduce the defect rate of a system (Brady and Allen 2006). The integration of these two methodologies for continuous improvement of the organization is known as the lean six sigma framework (Pepper and Spedding 2010). A key data-driven approach for lean six-sigma is known as DMAIC (Define-Measure-Analyze-Improve-Control), which is an interconnected five-stage cycle for process improvement (Sokovic, Pavletic, and Pipan 2010).
Lean Six Sigma applied to process performance and improvement model for the development of electric scooter water-cooling green motor assembly
Published in Production Planning & Control, 2019
Ching-Hsin Wang, Kuen-Suan Chen, Kim-Hua Tan
As stated above, Lean Six Sigma has advantages of cutting waste and facilitating process improvements as well as system analysis, helping enterprises create the overall business benefits in the value chain. Used in the renewable energy industry, it can urge enterprises to perform well in the TBL sustainable production. In addition, in response to the environmental issues triggered by global warming, numerous companies put the factor of carbon emission into the consideration of production, developing green technology or adopting cleaner production aimed at sustainable development. Therefore, this work took the ‘electric scooter water-cooling green motor’ manufactured in Taiwan, a region with the world’s highest density of scooters (in 2017, the number of scooters was 806.56/km2), as a case study. The green motor produced by the case company combining the concepts of green energy and cleaner production differs from the general motor using air to cool down the high temperature generated by operation. Instead, the green motor adopts the water-cooling and circulating method to perform a more efficient cooling way, so that it can better the output efficiency of motor operation and reduce the impact on our environment. Lean Six Sigma can help to bring enterprises into harmony with economic benefits, ecological benefits and social benefits.