• Energy Research

The manifestation of new part designs and continuously changing market demands as well as the requirements of new functions and technologies often results in higher material cost, lesser machine utilization, and extensive wastage of energy. As a consequence, companies across the world are striving for sustainable manufacturing, which can ensure flexibility as well as adaptability, with higher productivity and lesser wastage of resources. The dynamic and competitive nature of the world market emphasizes the importance of economically sustainable setups, such as reconfigurable cellular manufacturing systems (RCMSs). Indeed, among several cutting-edge strategies, the RCMS is the most prominent owing to its versatility, rationality, and resilience. However, one of the limitations associated with RCMS is the evaluation and selection of the best configuration that can meet abrupt changes and achieve manufacturing sustainability. Therefore, organizations intending to reconfigure have to address the issue of evaluating all possible alternatives and selecting the best one using a well-defined methodology. This paper focuses on evaluating and finding the best configuration using multi-criteria decision-making (MCDM) approaches depending on PROMETHEE and VIKOR. The fuzzy analytic hierarchy process (FAHP) is utilized to compute the weights of various criteria because it also considers any uncertainty and vagueness existing in the problem. The assessing attributes in this study are selected by keeping in mind the objective of sustainable manufacturing. The two MCDM methods are utilized for ranking different configurations to ascertain the results obtained from the other. The study accomplished in this paper is related to manufacturing setups that need to be reconfigured. The number of manufacturing configurations is determined, and simulation models are established for each configuration. The simulation outcomes are examined using the FAHP-PROMETHEE and FAHP-VIKOR to assess the appropriateness of each configuration depending on the identified performance measures. The results of the experiments show the importance of employing MCDM in RCMS to achieve sustainable manufacturing and determining the most effective setup.

Global warming has led to rising electricity demands due to soaring cooling load, resulting in different technologies being implemented with renewable energy options. Renewable energy has been used to partially or fully operate these cooing systems through different technology routes in both conventional and hybrid modes. The feasibility of a particular cooling process is influenced by several technological, economic, environmental and other related factors. Selection of the appropriate route also requires consideration of external factors such as local weather, cooling load requirements and the potential of possible renewable energy. Multi-criteria decision analysis is a useful tool to systematically arrive at the right option from several possible options. This tool is used to assess the feasibility of eight technology routes for three different climatic conditions. Other than the direct cooling processes, two routes of renewable energy utilization, namely, the solar photovoltaic system and solar thermal system, are considered. The normalized decision matrix is established and weighted decision matrix is estimated, and the best solution and the worst solution values are obtained by using equations. This study is performed for three climatic zones under the Koppen classification, namely, the tropical maritime arid condition with average midday temperature from 40 to 45 °C, with two different relative humidity ranges, namely, dry area and maritime area. Additionally, the temperate continental climatic zone is analyzed for comparison. The results of this study will help decision makers to judiciously implement air conditioning systems in the above climatic zones. The distance of each waste treatment strategy from the overall best alternative treatment strategy and the overall worst alternative treatment strategy is obtained. Finally, the cooling strategies are ranked for the best option for the cooling mechanism to be adopted for the three climatic conditions.

Saudi Arabia has a 2030 Vision in which sustainability is a central pillar. Sustainability in manufacturing organizations has become a topic of discussion as a potential solution to help them survive and prosper in a competitive market. Here, the objective is to establish a sustainability indexing model for Saudi manufacturing organizations that will help organizations to prepare their sustainability reports in line with international sustainability standards. This study will also help Saudi manufacturing organizations evaluate their level of sustainability and identify barriers to improving their sustainability. The model presented has three sustainability dimensions, 12 criteria, and 29 sub-criteria. The model was implemented in a Saudi manufacturing organization as a case study. To improve the organization’s sustainability level, sustainability barriers were identified and analyzed. The model indicates that eight sub-criteria scored below the threshold value, which was found to be 0.19. These sub-criteria were further considered as sustainability barriers in the case organization.

Sustainability is a growing concern for manufacturing companies, as they are major contributors to pollution and consume a substantial portion of the world´s natural resources. Sustainable manufacturing can reduce waste, conserve energy and increase resource efficiency. However, one of the main challenges facing manufacturing organisations to put sustainability into practice is the lack of understanding of the cause-and-effect relationships between critical indicators of sustainable manufacturing. To overcome this challenge, a novel, rigorous and integrated framework, composed of four quantitative methods, is proposed to analyse critical indicators of sustainable manufacturing. The analysis is based on responses from both academic and industry experts. These four methods including DEMATEL (decision-making trial and evaluation laboratory), the MMDE (maximum mean de-entropy) algorithm, ISM (interpretive structural modelling) and SEM (structural equation modelling) are uniquely integrated to present statistically validated relationships between critical indicators using information on varying degrees of relationship between them. The final cause-and-effect models for the respondent groups (i.e., researchers and industry experts) are further validated through gathering the viewpoints of a researcher and an industry practitioner for its robustness. The novelty of our research lies in: (1) proposing a novel and integrated rigorous quantitative framework combined with qualitative research method; (2) applying the proposed framework to analyse contextual relationships between critical indicators of implementing sustainability, in the manufacturing sector as a whole, which to the best of authors’ knowledge is the first of its kind; and (3) comparing and contrasting results of researchers and industry practitioners’ groups along with a check of their validation and robustness.

Supply chain agility and sustainability is an essential element for the long-term survival and success of a manufacturing organization. Agility is an organization’s ability to respond rapidly to customers’ dynamic demands and volatile market changes. In a dynamic business environment, manufacturing firms demand agility to be evaluated to support any alarming decision. Sustainability is an aspect to sustain collaboration, value creation, and survival of firms under a dynamic competitive business scenario. Agility is a capability that drives competitiveness to foster sustainability aspects. The purpose of this article is to consider and evaluate the supply chain behavior within the context of Saudi enterprises. The efficacy and relevance of this model were explored through a case study conducted in a Saudi dairy manufacturing corporation. Owing to the complexity and a large number of calculations that are required for evaluating the agility of the supply chain, a decision support system was proposed as a tool to assess the supply chain and identifying barriers to a strategic sustainable solution for a specific organizational target. The decision support system is extensive as it contains six separate agility enablers and ninety-three agility attributes for the supply chain. The assessment was carried out using a fuzzy multi-criteria method. It combines the performance rating and importance weight of each agile supply chain-enabler-attribute. To achieve and sustain local and global success, the case organization strove to become a major local and global manufacturer to satisfy its customers, reduce its time to market, lower its total ownership costs, and boost its overall competitiveness through improving its agility across supply chain activities to foster sustainability for a manufacturing organization located in Saudi Arabia.

Agility has a special place in the start-up Industry 4.0 era. More research is required to properly comprehend the agile implications of start-up Industry 4.0 regarding the impact of digitization on the economy, the environment, and society. Investigating the effects of start-up 4.0 agility is still in its early stages. The current study simulates the variables impacting agility in start-up activities in Industry 4.0 to tackle this problem. In addition to the pre-arranged interview, a closed-ended questionnaire was used to gather information. In the context of start-up operations 4.0, the MICMAC technique is used to evaluate and categorize the components that contribute to agility in order to comprehend their interconnections. The research identified eleven characteristics of facilitating agility in start-up operations 4.0. Industry 4.0 concepts have significantly influenced large organizations but deploying agility in start-up 4.0 has been less visible. Hence, this study presents an innovative approach to incorporating agility in modern start-up operations. The significance of artificial intelligence, cloud computing, network and connectivity, technology, and digital twin in this context is evident. The research provides important light on the elements that contribute to the successful use of agility in start-up 4.0, offering useful insights for stakeholders and academics.

Energy recovery from municipal solid waste is one of the means to attain sustainable development. Multiple factors involving several location specific situations, both measurable and intangible, makes decision making for technology selection very difficult. In this paper, a multi criterion evaluation system for municipal solid waste treatment strategies is established on the basis of specific, measurable, attainable, relevant and trackable situations, to prove the effectiveness of this method. From among various alternatives, three prominent strategies, namely, incineration, anaerobic digestion and composting are considered for the evaluation. Exhaustive data collection is done from conducting field studies, as well as from published data. Three types of communities are evaluated by this technique, namely, typical cities in developed countries, ‘A’ grade cities in India and ‘B’ grade cities in India. The purpose of the study is to evaluate the effect of community specific situations on the right choice of waste disposal method using a technique for order of preference by similarity to ideal solution (TOPSIS) approach, where weights of criteria are determined by means of entropy weight method. The case study shows that the proposed evaluation results are reliable, which are more coincident with the reality, since the most relevant factors for selection have been used backed by exhaustive field data collection. Policy makers gain from the outcome of this study by guiding them through technology selection. So, the adopted approach should be promoted widely in the evaluation of waste treatment strategies, to realize sustainable development.

Awareness of the consequences of waste mismanagement has resulted in urban planners looking for effective disposal techniques with the added benefit of energy generation. The decision regarding an energy conversion technique to adopt on a community level is based on different technology assessment factors with maximum weightage on environmental effects. Gasification techniques in general and thermal gasification strategies in particular are appropriate methods when environmental impacts are to be minimized. Thermal gasification techniques have evolved with different configurations, syngas generation rates, and other advantages and disadvantages; hence, the selection of the right technique is essential, and establishing guidelines for decision-makers is necessary. The six different gasifiers considered in the present study were updraft gasifiers, downdraft gasifiers, cross-draft gasifiers, bubbling fluidized bed gasifiers, circulating fluidized bed gasifiers, and dual-bed fluidized bed gasifiers. The assessments performed in the present study are based on the attributes of the different techniques using the multi-criteria decision method. Multi-criteria decision analysis is an appropriate method proven to be an ideal procedure in these situations. Attribute values for gasifier performance, environmental effects, economic performance indices, and fuel requirements were determined from collected waste assessment data and published information. Analysis was performed for both recycling and non-recycling scenarios of waste utilization by applying different weight scenarios for the attributes. Results of the study indicate that downdraft gasifiers showed the best performance in terms of environmental effects under the recycling scenario, with 0.1% and 0.0125% by volume of carbon dioxide and methane emissions, and under the non-recycling scenario, with 0.125% and 0.02% by volume of carbon dioxide and methane emissions. Downdraft gasifiers had high overall rankings in performance when evaluated against different entropy weights for both scenarios. The results of the study can be applied to urban communities in different climatic regions as well as for different scales of operation.