Building Model-Driven Decision Support System in Product Redesign Plan

Abstract

Product recovery strategy requires a thoughtful consideration of environmental implications of operational processes, undergone by a manufactured product in its entire product lifecycle, from stages of material processing, manufacturing, assembly, transportation, product use, product post-use and end-of-life. At the returns stream from product use stage, those parts and/or component assemblies from a used product have several disposition alternatives for recovery, such as direct reuse, remanufacture, recycle or disposal. Due to such complexity of the manufacturing processes in recovery, current decision methodologies focus on the performance measures of cost, time, waste and quality separately. In this article, an integrated decision model for used product returns stream is developed to measure the recovery of utilisation value in the aspects of cost, waste, time, and quality collectively. In addition, we proposed a model-driven decision support system (DSS) that may be useful for manufacturers in making recovery disposition alternatives. A case application was demonstrated with the use of model-driven DSS to measure recovery utilisation value for the used product disposition alternatives. Finally, the future work and contributions of this study are discussed.Designs 2019, 3, 18 2 of 21 recovery utilisation potential for the used manufactured products [18][19][20][21][22][23][24][25][26]. The existing research on product recovery focuses on various aspects of post-use operations, including environmentally conscious manufacturing and product recovery operations, reverse logistics plan, green supply chain management, product redesign plan, sustainable supply chain management and 3R methodologies (i.e., reuse/remanufacture/recycle related activities) [3,[13][14][15][27][28][29].Many companies found the use of real-time communication to surpass expectations, therefore allowing them to effectively analyse different data streams and create new policies or processes that benefit the company as a whole. The manufacturing industry has far superseded any other industry with its improvements on effectiveness and efficiency after implementing the advanced decision support system and communication technologies. The information age saw a shift in consumer behaviour, from physical purchases to online ones. These consumer behaviours have additionally forced businesses to rethink and reshape the methods in which they perform everyday processes, communicate with customers and plan for future events. This also includes the product lifecycle management for manufacturers by considering actual performance measures of used product in the aspects of cost, time, waste and quality.In today's dynamic environment, substantial interest in sustainability by customers, businesses owners, governments, and community awareness is also driving many sectors in the manufacturing industries to engage with product recovery strategy and its implementation. Until now, numerous industry practitioners are still struggling with product redesign plans from ...

Digital twin for product versus project lifecycles’ development in manufacturing and construction industries

“…In the final phase of the manufacturing product lifecycle, recycle and disposal refers to the disposal or reuse of a product after it has been used by the customers (Son et al, 2022). Manufacturers are currently facing significant challenges in the disposal of used products, therefore it is important to explore ways to reuse, remanufacture and recycle products or their components during the product lifecycle (Kuik & Diong, 2019). In this phase, combined with deep learning, the utilisation of digital twin can provide manufacturers with information to make inform decisions on whether to remanufacture, upgrade or repair products (Zacharaki et al, 2021).…”