Production Enhancement through Integration of Lean, Life Cycle Assessment & Industry 4.0

• Main Authors: Tehrim Ijaz, Syed Mustafa Haider, Muhammad Zeeshan Rafique, Syed Hadika Jamshaid, Muhammad Ismail
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2023
• Online Access: http://journalarticle.ukm.my/22198/1/kjt_23.pdf; http://journalarticle.ukm.my/22198/; https://www.ukm.my/jkukm/volume-3503-2023/
• Institution: Universiti Kebangsaan Malaysia

Advancement in the manufacturing sector has attained a dominate interest from the researchers as well as the industrialists, for attaining the more products efficiencies. The concept of Lean Manufacturing set the cornerstone for excellence in manufacturing sector by improving the production times and reducing the non-value-added processes. In 2011, the concept of Industry 4.0 pivoted the concept of automation in factories to complement the production improvement processes. The under developing countries such as Pakistan, the manufacturing sector is run with the conventional manufacturing practices, which yields the products of lower quality and much time is being wasted resulting in overall poor efficiency. Moreover, those industries which want to improve their processes are not very much certain, about the methodologies they shall implement. In this research study, the authors have used the mathematical modelling approach of Analytical Hierarchy Processes (AHP) to recognise the pertinent Industry 4.0 technologies and lean perceptions – this technique empowers opportunity of organizing and analysing the intricate decisions for a strong understanding. By using Value Stream Mapping and Automation in a simulation-based case study, improvements of 44.70% in lead time, 17% in value added time and 45.25% in non-value-added time were witnessed. This research explores the avenue of Multi-Criteria Decision-Making (MCDM), based decision making in Industry 4.0 related environments. It will provide clarity to academicians regarding the integration of lean and Industry 4.0 through optimized and logical selection of relevant approaches, in addition to aiding practitioners in intelligent decision making.