Optimisation of a sustainable manufacturing system design using the multi-objective approach

Abstract

The main contributions of this research 1) The concept of lean methods does not include environmental considerations in terms of such as energy consumption and CO 2 (carbon dioxide) emissions, which are also important factors today for developing a sustainable manufacturing system. This research addresses these issues involved in modelling a sustainable manufacturing system allowing an evaluation in energy consumption and CO 2 emissions against the total cost using the multi-objective approach. This a novel approach proposed in this study which has not explored in the current literature. 2) This research presents a development of a multi-objective model of a sustainable manufacturing system design in which three facilities were considered, these are supplier s, factory f and warehouse w in order to option the optimal solution among conflicting objective including investment cost for establishing the manufacturing system, total energy consumption consumed by the manufacturing system and total CO 2 emissions released from it. 3) The developed model can be used for designing the sustainable manufacturing system by taking into account the economic and ecological parameters towards a minimization of the total cost, the total energy consumption and CO 2 emissions associated with relevant machines, air conditioning units and lighting bulbs involved in each manufacturing process and material flow. 4) The developed model was coded using LINGO 11 in which optimal solutions were obtained using two different solution approaches which are the ε-constraint approach and the LP-metrics approach, respectively. Subsequently, the performances of these approaches were compared in terms of both the solution quality and run time required. The best solution then was determined using the max-min approach. This helps in obtain the best sustainable manufacturing system design and it also reflects different prospects of decision makers or manufacturing system designers in different preferences. 5) Applicability of the developed model and proposed solution approaches was examined using collected data from a real case study. 6) The study concluded that the multi-objective mathematical model was useful as an aid for optimizing the manufacturing system design under the economic and ecological constraints.

Gresilient supplier assessment and order allocation planning

“…With the recognition of resource depletion, companies are ever increasingly required to consider the environmental impact of their supply chain (Koberg and Longoni, 2018;Rezaei et al, 2017;Nujoom et al, 2018Nujoom et al, & 2019andMohammed et al, 2017 &2019). Green supply chain management understands and accounts for the full range of purchasing, production, marketing, packaging and logistical activities from an environmental perspective (Burinskiene et al, 2018;Sarkis, 1999).…”

A hybrid MCDM-FMOO approach for sustainable supplier selection and order allocation

“…Sustainable issues have become a mandatory part of the sustainable growth, which is one of the major concern for enterprises these days. The environmental issues have been addressed as a major issue at the recent United Nations Conference on the Sustainable Development (Fahimnia et al, 2015;Nujoom et al, 2017Nujoom et al, & 2018. Besides, the growing interests in the sustainable growth increases the challenges for a decision maker in selecting the sustainable suppliers in which takin into account economic, environmental and social aspects.…”

Sustainable Manufacturing Technologies: A Systematic Review of Latest Trends and Themes

“…Manufacturing system and process design technologies were placed at the foundation of sustainable manufacturing, enabling holistic analyses for designing sustainable manufacturing systems and processes that will proactively support constructing manufacturing entities that are "sustainable-first-time" and contribute to our transition towards SM. Various system and process optimisation techniques [164], tools [109], selection methodologies [133], roadmaps [101], CAD methodologies [165], and models [166] to support this have been offered to date.…”