Integration of Data-Driven Process Re-Engineering and Process Interdependence for Manufacturing Optimization Supported by Smart Structured Data

Khan, Md Ashikul Alam and Butt, Javaid and Mebrahtu, Habtom and Shirvani, Hassan and Sanaei, Alireza and Alam, Md Nazmul (2019) Integration of Data-Driven Process Re-Engineering and Process Interdependence for Manufacturing Optimization Supported by Smart Structured Data. Designs, 3 (3). p. 44. ISSN 2411-9660

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Official URL: https://doi.org/10.3390/designs3030044

Abstract

Process re-engineering and optimization in manufacturing industries is a big challenge because of process interdependencies characterized by a high failure rate. Research has shown that over 70% of approaches fail because of complexity as a result of process interdependencies during the implementation phase. This paper investigates data from a manufacturing operation and designs a filtration algorithm to analyze process interdependencies as a new approach for process optimization. The algorithm examines the data from a manufacturing process to identify limitations through cause and effect relationships and implements changes to achieve an optimized result. The proposed cause and effect approach of re-engineering is termed the Khan-Hassan-Butt (KHB) methodology, and it can filter the process interdependencies and use those as key decision-making tools. It provides an improved process optimization framework that incorporates data analysis along with a cause and effect algorithm to filter out the process interdependencies as an approach to increase output and reduce failure factors simultaneously. It also provides a framework for filtering the manufacturing data into smart structured data. Based on the proposed KHB methodology, the study investigated a production line process using the WITNESS Horizon 22 simulation package and analyzed the efficiency of the proposed approach for production optimization. A case study is provided that integrated the KHB methodology with data-driven process re-engineering to analyze the process interdependencies to use them as decision-making tools for production optimization.

Item Type: Journal Article
Keywords: process re-engineering, manufacturing processes, structured data, smart structured data, cause and effect re-engineering, process optimization framework, process interdependencies, cause and effect algorithm
Faculty: Faculty of Science & Engineering
Depositing User: Mr Md Ashikul Alam Khan
Date Deposited: 27 Aug 2019 10:34
Last Modified: 14 Nov 2019 16:07
URI: http://arro.anglia.ac.uk/id/eprint/704669

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