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Productivity enhancement: lean manufacturing performance measurement based multiple indicators of decision making
- Source :
- Production Engineering. 15:343-359
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- Developing an appropriate performance measurement system to foster continuous improvement can be challenge due to the company’s strategy and diversity of characteristics. This paper aims to develop performance measurement systems (PMS) for productivity enhancement of a particularly lean company or organisation. The PMS is based on multiple indicators decision making (MIDM) and uses the fuzzy analytical hierarchy process (FAHP). The hierarchical levels by choosing the perspectives and indicators were employed the fuzzy vagueness and uncertainty in human judgment into crisp scores from pair-wise comparison as decision making. Hierarchical mechanisms and multiple indicator of performance can create a link between tactical operational processes and strategic levels. It may assist a company in terms of measuring progress toward its goals, allowing decisions to be made regarding strategic management and operational activities, which will lead to continuous improvement. The PMS framework accommodates the company’s performances to enhance their productivity. A case study was performed to explore the applicability and potential strength of the lean PMS model.
- Subjects :
- 0209 industrial biotechnology
Process management
Computer science
Mechanical Engineering
Vagueness
02 engineering and technology
Fuzzy logic
Lean manufacturing
Industrial and Manufacturing Engineering
020303 mechanical engineering & transports
020901 industrial engineering & automation
0203 mechanical engineering
Production (economics)
Performance measurement
Strategic management
Productivity
Diversity (business)
Subjects
Details
- ISSN :
- 18637353 and 09446524
- Volume :
- 15
- Database :
- OpenAIRE
- Journal :
- Production Engineering
- Accession number :
- edsair.doi...........a42711144a3441ea7acbe405212b2a0b
- Full Text :
- https://doi.org/10.1007/s11740-021-01025-7