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Hardware Design
Published in Richard C. Fries, Handbook of Medical Device Design, 2019
Genichi Taguchi developed a framework for statistical design of experiments adapted to the particular requirements of engineering design. Taguchi suggested that the design process consists of three phases: system design, parameter design, and tolerance design. In the system design phase, the basic concept is decided, using theoretical knowledge and experience to calculate the basic parameter values to provide the performance required. Parameter design involves refining the values so that the performance is optimized in relation to factors and variation which are not under the effective control of the designer, so that the design is robust in relation to these. Tolerance design is the final stage, in which the effects of random variation of manufacturing processes and environments are evaluated, to determine whether the design of the product and the production processes can be further optimized, particularly in relation to cost of the product and the production processes.
Overview of Lean for Hospitals and Health Systems
Published in Mark Graban, John Toussaint, Lean Hospitals, 2018
Six Sigma is a “disciplined, data-driven approach and methodology” for improving quality and processes by reducing defects and variation.44 The term refers to six standard deviations around a mean, where reaching that level means only 3.4 defects per million opportunities in a process.45 Six Sigma is known for the DMAIC model, of define, measure, analyze, improve, and control. Those who are trained and certified in Six Sigma practices receive “belts” of various colors, signifying their level of knowledge and experience. Created at Motorola as an extension of TQM, Six Sigma was popularized by General Electric (GE) and was introduced to healthcare in the mid-1990s through GE Healthcare. Some organizations, like ThedaCare and Virginia Mason Medical Center, follow Toyota’s example by eschewing formal Six Sigma, as they combine Lean and the seven basic tools of TQM. Other health systems utilize both Lean and Six Sigma, often under the banner of “Lean Six Sigma” or “Lean Sigma.” Some differentiate Lean as being something you can teach to everybody and use as a management system, while giving detailed Six Sigma training to a small number of experts who are utilized to solve particularly difficult quality or process problems. Well-known health systems that use Lean Sigma include Cleveland Clinic and Johns Hopkins.
Hardware Development Methods and Tools
Published in Paul H. King, Richard C. Fries, Arthur T. Johnson, Design of Biomedical Devices and Systems, 2018
Paul H. King, Richard C. Fries, Arthur T. Johnson
Genichi Taguchi developed a framework for statistical design of experiments adapted to the particular requirements of engineering design. Taguchi suggested that the design process consists of three phases: system design, parameter design, and tolerance design. In the system design phase, the basic concept is decided, using theoretical knowledge and experience to calculate the basic parameter values to provide the performance required. Parameter design involves refining the values so that the performance is optimized in relation to factors and variation which are not under the effective control of the designer, so that the design is robust in relation to these. Tolerance design is the final stage, in which the effects of random variation of manufacturing processes and environments are evaluated, to determine whether the design of the product and the production processes can be further optimized, particularly in relation to cost of the product and the production processes.
Modification of ARL for detecting changes on the double EWMA chart in time series data with the autoregressive model
Published in Connection Science, 2023
Kotchaporn Karoon, Yupaporn Areepong, Saowanit Sukparungsee
The control chart is widely used in the fields of finance, business, engineering, healthcare, and others to track processes and detects sudden changes in the mean or variance of those processes, especially in the field of industries (Fugen, 2019; Zhang et al., 2022). Using control charts, it is possible to distinguish between common and unique sources of process variation and handle each case separately. The control limits on control charts are determined by common factors. Control charts provide precise instructions on how and when to modify a process. Nowadays, control charts are an essential tool in SPC, and their industrial significance lies in their ability to monitor and control process variability, improve process efficiency, reduce costs, ensure product quality, and support decision-making. There are many types of research that were presented that utilised the control chart in the field of industries. Shrestha (2021) used a control chart to control the sausage manufacturing process. Tegegne et al. (2022) used a control chart to decide on quality control during the production process in their case study of the Ethiopian cement industry, and so on.
Investigation of critical success factors for improving supply chain quality management in manufacturing
Published in Enterprise Information Systems, 2021
Ka-Yin Chau, Yuk Ming Tang, Xiaoyun Liu, Yun-Kit Ip, Yiran Tao
The supply chain involves a set of activities from procurement to ultimate customer delivery (Beamon and Ware 1998), which may be disrupted by an unsmooth supply chain process. SCQM requires external and internal business process integration across the whole supply chain (Fernandes et al. 2017). The key business processes integration by providing products and services information not only to enhance efficiency but also to add value to the trading partners. Process integration decreases process variation resulting in continuous quality improvement (Azar, et al., 2010). The degree of process integration decides the degree of efficiency and effectiveness of the supply chain (Chin et al. 2004). Improving the quality of all supply chain processes can result in lower costs and in maximising resource use (Beamon and Ware 1998). The case study Company is a typical manufacturing company that involves various activities and processes. This study therefore hypothesised: H4: There is a positive relationship between process integration and improvement of SCQM in the Company.
Identifying dominant causes using leveraged study designs
Published in Quality Engineering, 2021
Mahsa Panahi, Jeroen De Mast, Stefan H. Steiner
A common challenge for industrial engineers is to reduce manufacturing variation, since in modern manufacturing, tolerances for characteristics such as dimensions are extremely tight. Usually, variation problems are caused by a large number of variation sources, such as variability in materials, manufacturing conditions, measurement, etc. Among these causes, there are usually a few having a disproportionate impact on the total variation, while there are many whose contribution to the total variation is only marginal (De Mast et al., 2019). Juran named this principle after Pareto, and he talked about the "vital few" causes, which are few in number but account for almost all of the total variation, and the "trivial many" causes, which are large in number, but even their combined contribution is often negligible (Gryna and Juran, 1988).