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Lean Manufacturing and Six Sigma : Behind the Mask

By: Contributor(s): Material type: TextTextPublication details: IntechOpen 2020Description: 1 electronic resource (174 p.)ISBN:
  • 9781789239089
Subject(s): Online resources: Summary: Lean Manufacturing, also called lean production, was originally created in Toyota after the Second World War, in the reconstruction period. It is based on the idea of eliminating any waste in the industry, i.e. any activity or task that does not add value and requires resources. It is considered in every level of the industry, e.g. design, manufacturing, distribution, and customer service. The main wastes are: over-production against plan; waiting time of operators and machines; unnecessary transportation; waste in the process itself; excess stock of material and components; non value-adding motion; defects in quality. The diversity of these issues will be covered from algorithms, mathematical models, and software engineering by design methodologies and technical or practical solutions. This book intends to provide the reader with a comprehensive overview of the current state, cases studies, hardware and software solutions, analytics, and data science in dependability engineering.
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Lean Manufacturing, also called lean production, was originally created in Toyota after the Second World War, in the reconstruction period. It is based on the idea of eliminating any waste in the industry, i.e. any activity or task that does not add value and requires resources. It is considered in every level of the industry, e.g. design, manufacturing, distribution, and customer service. The main wastes are: over-production against plan; waiting time of operators and machines; unnecessary transportation; waste in the process itself; excess stock of material and components; non value-adding motion; defects in quality. The diversity of these issues will be covered from algorithms, mathematical models, and software engineering by design methodologies and technical or practical solutions. This book intends to provide the reader with a comprehensive overview of the current state, cases studies, hardware and software solutions, analytics, and data science in dependability engineering.

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