Agile Manufacturing System Research Articles

Stakeholders’ perspectives and performance outcomes of sustainable market-focused manufacturing system in Indian manufacturing organizations

Sustainability and the ever-changing customer demands are the key drivers for innovation across product, process, system, and supply chain management. Sustainability innovations aim to improve organizational environmental, social, and economic performance. Given the complexity of sustainability and ever-changing business and stakeholders’ requirements, organizations must focus their innovation in the direction of meeting the requirements of their stakeholders and business. Integrated sustainable green lean six sigma agile manufacturing system (ISGLSAMS) is a sustainable market-focused manufacturing system. It provides a sustainability and market-oriented business model and meets the perspectives of the various stakeholders. This study aims to identify and rank the various performance outcomes of ISGLSAMS. The study also explores the correlations among the various performance outcomes of ISGLSAMS. The study helps the practitioners to better understand the ISGLSAMS and stakeholders’ perspectives of ISGLSAMS. This research provides a foundation for practitioners, policymakers, organizations, and value chain partners (i) to formulate policies and roadmaps for the successful adoption of ISGLSAMS and (ii) for fostering a more sustainable development of manufacturing organizations in India.

Corrigendum to “Drivers for the adoption of integrated sustainable green lean six sigma agile manufacturing system (ISGLSAMS) and research directions” [Clean. Eng. Technol. 7 (2022) 1–30/100449

Corrigendum to “Drivers for the adoption of integrated sustainable green lean six sigma agile manufacturing system (ISGLSAMS) and research directions” [Clean. Eng. Technol. 7 (2022) 1–30/100449

Drivers for the adoption of integrated sustainable green lean six sigma agile manufacturing system (ISGLSAMS) and research directions

Due to the scarcity of resources, and the need for preserving the resources for the future generation, there has been significant growth in research and development in a sustainable market-focused manufacturing system, in particular with the view of product recovery, waste elimination, and landfill legislation. It has extended the responsibility of manufacturing organizations to include the recovery and safe disposal of their product, process, and supply chain waste, as well as, the adoption of a sustainable quick response manufacturing system, to produce sustainable customized products. A more compatible manufacturing system and strategy are required to meet these business goals. It is observed through literature that an integrated sustainable green lean six sigma agile manufacturing system (ISGLSAMS) provides a strong platform to meet all these business, societal and ecological needs under a single umbrella. However, many organizations opt for this strategy voluntarily and many do not. It is observed through a literature survey that through this strategy organizations improve their financial, market, social, environmental, operational, and sustainable performance. The main objective of this review is to identify the various drivers for the adoption of an ISGLSAMS, so that governments, stakeholders, and policymakers may plan the strategy for motivating the organizations for the ISGLSAMS. The review also discusses the key enablers and characteristics of ISGLSAMS, product, and strategy. The review also highlights the key characteristics, and clauses of each driver, and research areas for the drivers for the adoption of ISGLSAMS. The review also shows a performance measurement or performance benchmark framework for ISGLSAMS.

Selecting the most agile manufacturing system with respect to agile attribute-technology-fuzzy AHP approach

Selecting the most agile manufacturing system with respect to agile attribute-technology-fuzzy AHP approach

Structural Equation Modeling of Barriers to the Adoption of Integrated Sustainable Green Lean Six Sigma Agile Manufacturing System (ISGLSAMS) in Indian Manufacturing Organizations

Structural Equation Modeling of Barriers to the Adoption of Integrated Sustainable Green Lean Six Sigma Agile Manufacturing System (ISGLSAMS) in Indian Manufacturing Organizations

Selecting the most agile manufacturing system with respect to agile attribute- technology- Fuzzy AHP approach

Selecting the most agile manufacturing system with respect to agile attribute- technology- Fuzzy AHP approach

An optimised framework for implementation of hybrid lean and agile manufacturing systems in rolling industry for India

The rolling manufacturing companies play an important role in manufacturing of sheet metals and applications of lean and agile manufacturing industry in an integrated form consequence to yield better performance and results. The common factors of a lean and agile manufacturing system were analysed by weighted interpretive structural modelling (W-ISM) approach. ISM approach is well suited for demonstrating the implementation of lean and agile manufacturing concepts in several aspects of the rolling industry while the comprehensive index (CI) further augments the recognition of such key factors. The analysis of CI value will help the managers from the rolling industry in implementing the lean-agile manufacturing systems.

Supply–Demand Prediction for Agile Manufacturing with Deep Neural Network

Abstract Agile manufacturing represents modern production systems that rapidly respond to a fast-moving marketplace and connect customers to production. The success of an agile manufacturing system relies on multisource data analytics, which provide smart data-driven decision-making strategies to guide manufacturing and the supply chain system. In order to implement rapid manufacturing processes to respond to customer orders, supply–demand gap prediction plays a critical role. In this article, we study the problem of predicting supply–demand gap with respect to product types, categories, and spatiotemporal attributes. To this end, we propose and develop an end-to-end framework using an extendable deep neural network architecture for supply–demand gap reduction. The framework can process multiple customized input factors and automatically discover spatiotemporal supply–demand patterns from historical transaction data. A set of customized features are employed to build a general training model to predict future demand. Embedding layers are used to map high dimensional features into a smaller subspace for input data consolidation. Fully connected layers with activation functions are used to build the training architecture of the model. Customized data attributes can be concatenated from different layers in the deep learning neural network. In this way, multisource input data can be integrated with outputs of internal layers for a comprehensive demand prediction. Experiments were conducted to evaluate the network with real supply and demand data, which were acquired from warehouses of a manufacturing company. The experimental results demonstrated that the proposed network was able to reduce supply–demand gap and provide a practical solution to long-term customer demand prediction.

Analysis of how agile manufacturing capabilities could be used differently in plants within the footloose and rooted subnetworks of the global production network

This paper provides a literature review study to investigate how Agile Manufacturing (AM) capabilities could be used in different plants within a company's Global Production Network (GNP). To do this, this paper makes use of Ferdows, Vereecke, and De Meyer (2016) subnetworks positions framework. Each of the subnetwork positions has its own manufacturing characteristics and missions. From the four subnetworks, this paper focused on the main two, footloose and rooted. 17 articles were analyzed and this paper found that there are four major AM capabilities categories, namely responsiveness, flexibility, integration, and competency. Each of the AM capabilities categories could be used differently in each of the subnetworks depending on the focus factors emphasized in each category. With that, this paper has presented how AM system capabilities could help plants in the footloose and rooted subnetworks to achieve their missions. Further, this study provides an early phase to understand how AM system could accommodates different plants positions in the GPN. This study also set out an insight that, despite being founded 29 years ago, AM system with their capabilities, is still relevant to be continuously implemented in the present time. This paper does not provide any empirical validation yet for the findings. Thus, this paper also provide avenues for future research.

Superiority of Fuzzy AHP-VIKOR approach in an agile environment

Agile manufacturing (AM) system focuses on the customised production with shorter lead time in a cost effective manner. Conceptual design is a vital phase of product development and AM obliges towards it. Selecting appropriate conceptual design often involves consideration of multiple factors, multi criteria decision making (MCDM) techniques facilitates in resolving this problem. In this study, hybrid fuzzy analytical hierarchical process (AHP) and fuzzy VIKOR approach was used for selecting the best conceptual design of instrument panel (IP). The article focuses on development of various concept designs for IP considering the recent manufacturing and technological aspects. Appropriate agile criteria were identified through several brainstorming sessions conducted among the stakeholders of the organisation. Fuzzy AHP model was used to compute the weights of the proposed conceptual designs and fuzzy VIKOR was used to select the best suited conceptual design. The case study was also practically validated in a manufacturing scenario.

Modelling and analysis of barriers affecting the implementation of lean green agile manufacturing system (LGAMS)

Purpose Many types of research have already investigated the lean, green or agile manufacturing systems in a discrete manner or as combinations of two of them. In today’s competitive scenario, if industry wants to perpetuate its name in the market, then it has to supervene proper thinking and smart approach. Therefore, the combination of lean, green and agile manufacturing systems can provide better and beneficial results. The purpose of this paper is to discern the barriers to the combined lean green agile manufacturing system (LGAMS), understand their interdependence and develop a framework to enhance LGAMS by using total interpretive structural modeling (TISM) and MICMAC (Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement) Analysis. Design/methodology/approach This paper uses TISM methodology and MICMAC analysis to deduce the interrelationships between the barriers and rank them accordingly. A total of 13 barriers have been identified through extensive literature review and discussion with experts. Findings An integrated LGAMS has been presented that balances the lean, green and agile paradigms and can help supply chains become more efficient, streamlined and sustainable. Barriers are identified while referring to all three strategies to showcase the clear relevance. TISM models the barriers in different levels showcasing direct and important transitive relations. Further, MICMAC analysis distributes the barriers in four clusters in accordance with their driving and dependence power. Research limitations/implications The inferences have been drawn from a model developed on the basis of inputs from a small fraction of the industry and academia and may show variations when considering the whole industry. Practical implications The outcome of this research can contribute to bringing the change to the manufacturing systems used in most developing nations. Also, top managers considering adoption of LGAMS can be cautious of the most influential barriers. Originality/value A TISM-based model of the barriers to an integrated LGAMS has been proposed with evaluation of the influence of the barriers.

A three-dimensional-printing-based agile and ubiquitous additive manufacturing system

Abstract Mass producing items using three-dimensional (3D) printing is challenging. This study exploits this technology for mass production by developing an agile and ubiquitous additive manufacturing system based on 3D printing. The proposed system receives an order and then distributes the order among multiple 3D printing facilities to minimize the makespan (i.e., cycle time). A decision-making model was also constructed for distributing the order to multiple 3D printing facilities to minimize the makespan, and an algorithm was developed to solve the model. The effectiveness of the proposed methodology was evaluated through an experiment. The experimental results showed that the proposed methodology reduced the cycle time by 54 min on average. Additionally, it could also distribute orders and balance the workloads of multiple 3D printing facilities. The proposed system is an industrial Internet of things–based technology that coordinates multiple distributed 3D printing facilities via the Internet. Its application to the mass production of 3D-printed items is efficient and economical.

An integrated approach for implementation of agile manufacturing system in an Indian manufacturing industry

PurposeThe advent of globalization not only made the manufacturing sector highly competitive but also facilitated best-quality products. The trend is further augmented by e-Commerce which increases the penetration to the targeted customer with the easy availability of customized product. In this backdrop, Indian manufacturing industries are striving hard to seek out best systems which will yield maximum profitability. Time is ripe to realize the true potential of agile manufacturing system (AMS). Infusion of AMS in manufacturing industry will bring forth the elusive mix of customer needs and products at lowest possible cost. But adoption and implementation of AMS is a challenging task in itself. There are certain facilitators and criteria which not only facilitate the system but also help in the effective and smooth implementation of this system. The purpose of this paper is to identify the criteria to weightage and ranking to AMS facilitators. This study was carried out by different approaches, namely, entropy approach, multi-objective optimization on the basis of ratio analysis (MOORA) method, Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis and a cross-sectional survey of manufacturing firms in India.Design/methodology/approachThe criteria and facilitators are identified followed by the application of entropy approach, MOORA method and VIKOR analysis to study and analyze the criteria weight and provide the ranking to AMS facilitators.FindingsThe result of the entropy approach concludes that beneficiary and non-beneficiary criteria carry 48.43 and 51.56 percent weight, respectively. MOORA method and VIKOR analysis conclude that organization structure and virtual enterprise facilitators are carrying the first and second rank, respectively.Research limitations/implicationsThis study is completed on the basis of responses from few experts from industry and academicians who may not reflect the attitude of entire industry community.Practical implicationsThis research is expected to facilitate policy makers in government and industries to frame policies for optimum utilization of resources and infrastructure for better performance. This paper helps the researcher to do a case study on the implementation of AMS and then finally helps to society in getting the high-quality product in an easy way.Originality/valueIntegration of entropy approach, MOORA method and VIKOR analysis with identification of AMS criteria weightage and ranking to AMS facilitators has been recommended for an industry which is an innovative effort for the execution of AMS.

An integrated fuzzy-based multi-criteria decision-making approach for the selection of an effective manufacturing system

PurposeThe research paper presents analysis and prioritization of barriers influencing the improvement in the effectiveness of manufacturing system. The purpose of this paper is to develop an integrated fuzzy-based multi-criteria decision-making (F-MCDM) framework to assist management of the case company in the selection of most effective manufacturing system. The framework helps in prioritizing the manufacturing systems on the basis of their effectiveness affected by the barriers.Design/methodology/approachIn this paper, on the basis of experts’ opinion, five barriers have been identified in a brain-storming session. The problem of prioritization of manufacturing system is a multi-criteria decision-making (MCDM) problem and hence is solved by using the F-MCDM approach using dominance matrix.FindingsManufacturing systems’ effectiveness for Indian industries is influenced by barriers. The prioritization of manufacturing systems depends on qualitative factor decision-making criteria. Among the manufacturing systems, leagile manufacturing system is given the highest priority followed by lean manufacturing system, agile manufacturing system, flexible manufacturing system and cellular manufacturing system.Research limitations/implicationsThe selection of an appropriate manufacturing system plays a vital role for sustainable growth of the manufacturing company. In the present work, barriers which influence the effectiveness of manufacturing system have been identified. On the basis of degree of influence of barriers on the effectiveness of the manufacturing system, five alternative manufacturing systems are prioritized. The framework will help the management of the case company to take reasonable decision for the adoption of the appropriate manufacturing system.Practical implicationsThe results of the research work are very useful for the manufacturing companies interested in analyzing the alternative manufacturing systems on the basis of their effectiveness and their sensitivity toward various barriers. The management of Indian manufacturing company will take decision to adopt a manufacturing system whose effectiveness is least sensitive toward barriers. Effectiveness of such manufacturing system will improve with time without having retardation due to barriers. With improved effectiveness of the manufacturing system, the manufacturing company would be able to survive with global competition. The result of the present work is based on the inputs from the case company and may vary for the other manufacturing company. In the present work, only five alternative manufacturing systems and five barriers have been considered. To obtain the better result, MCDM approach with more number of alternative manufacturing systems and barriers might be considered.Originality/valueThe research work is based on the fuzzy analytic hierarchy process framework and on the case study conducted by the authors. The work carried out is original in nature and based on the real-life case study.

An updated literature review of agile manufacturing: classification and trends

In contemporary manufacturing area, agility is considerably acknowledged as an emerging issue to react to dynamic market environment changes. The implementation of agile manufacturing system proved to be efficient to acquire a competitive advantage. Since the agile manufacturing (AM) concept was popularised in 1991, there is a growing recognition by practitioners and academics. The aim of this study is to perform an analysis of AM research in order to update the literature review, give the current discussion regarding the trends and note the suggestions for the future directions of AM research. In this paper, we provide a wide coverage of excessively citations on AM from 1991 to 2015. The papers are classified in AM conceptual frameworks, agility assessment, agility achievement, merging lean and agile concepts, and adopting AM on small- and medium-sized enterprises. Furthermore, a category scheme to organise the journals is proposed and equipped by summary statistics presentation. The study results of the literature review are expected to assist development in the AM research.

Evaluating key performance indicators of leagile manufacturing using fuzzy TISM approach

Leagile manufacturing strategy has emerged as one of the important strategy adopted by most of manufacturing organizations now a days. It has advantages of both lean as well as agile manufacturing system. Lean manufacturing tries to eliminate all different types of wastages like overproduction, inventory, unnecessary motion etc., while agile manufacturing focus on changing the production system as per the requirements of the customer and provide customized products within short span of time. Lean manufacturing focuses on no inventory and try to implement Just in Time methodology but for the system to be agile, there should be at least some inventory in store so that production can be started as soon as customer order is achieved. In this paper, key performance indicators (KPI) of leagile manufacturing are found by literature review and in consultation of experts and academicians working in the concerned field. Fuzzy TISM approach has been applied to find levels of different KPI’S. MICMAC analysis has been made to analyze the KPI’S and categorize them as autonomous, dependent, linkage, independent etc. on the basis of driving and dependence power. Finally, digraph is drawn to show relationship between various KPI’s.

A framework to enhance agile manufacturing system

PurposeThe purpose of this paper is to identify and analyze the interactions among different enablers of agile manufacturing system (AMS). The existing enablers available in the past literature are scattered and not able to meet specific requirements of the customers. So, it becomes a necessity to encapsulate these enablers in appropriate proportions to enable traditional organizations to AMS. To fill this gap total interpretive structural modeling (TISM) and MICMAC analysis-based framework model have been developed to understand the mutual interactions between among the enablers.Design/methodology/approachIdentification of enablers followed by application of TISM, which is an innovative version of ISM and MICMAC analysis, is used to study and analyze the mutual interactions between identified enablers.FindingsThe result reveals that top management support, organizational structure and information technology integration have strong driving power and weak dependence power and are at the lowest level in the TISM model hierarchy, while the outcome enablers of AMS have low-driving power but have high-dependence power.Research limitations/implicationsThis model is developed on the basis of inputs from few experts and may not reflect the opinion of whole industry community.Practical implicationsTop management must stress on enablers having strong driving power for efficient implementation of AMS. Managers in the area of manufacturing may drive useful insights from the empirical study presented in this paper. Managers should plan an effective strategy for proper implementation of AMS which makes organization more agile, productive, competitive and profitable.Originality/valueTISM-based framework structural model has been proposed for industry or organization which is a new effort for implementation of AMS.

Modelling manufacturing system effectiveness: an integration of analytical hierarchy process and linear programming

Manufacturing system effectiveness depends on several factors which include qualitative as well as quantitative factors. In the present paper, the management of the case company has to take a decision about the prioritisation of manufacturing systems on the basis of their effectiveness and has to decide about their production capacity. In the available literature, approaches like linear programming and AHP, mixed integer linear programming, and goal programming have been applied by some authors to tackle similar type of problems. These techniques are mathematical in nature and also consider qualitative factors which are crucial in determining the effectiveness of any manufacturing system, particularly when manufacturing systems are to be prioritised. The result from the research work with AHP framework indicates higher manufacturing effectiveness to leagile manufacturing system followed by agile manufacturing system, lean manufacturing system and flexible manufacturing system.

Modelling manufacturing system effectiveness: an integration of analytical hierarchy process and linear programming

Manufacturing system effectiveness depends on several factors which include qualitative as well as quantitative factors. In the present paper, the management of the case company has to take a decision about the prioritisation of manufacturing systems on the basis of their effectiveness and has to decide about their production capacity. In the available literature, approaches like linear programming and AHP, mixed integer linear programming, and goal programming have been applied by some authors to tackle similar type of problems. These techniques are mathematical in nature and also consider qualitative factors which are crucial in determining the effectiveness of any manufacturing system, particularly when manufacturing systems are to be prioritised. The result from the research work with AHP framework indicates higher manufacturing effectiveness to leagile manufacturing system followed by agile manufacturing system, lean manufacturing system and flexible manufacturing system.

An Enhanced Intelligent Water Drops Algorithm for Scheduling of an Agile Manufacturing System

This paper deals with an agile manufacturing system with two stages where the first stage is the machining stage including a single flexible machine while the second stage is assembly stage including parallel identical assembly machines. Products have an assembly structure where their parts should be processed at the first stage and then proceed to the assembly stage. The goal is to find the parts sequence which minimizes makespan. Since the studied problem is NP-hard, enhanced intelligent water drops (EIWD) algorithm as a new swarm-based nature inspired optimization algorithm is proposed. Also, artificial immune system (AIS) algorithm has been proposed to tackle the addressed problem. Computational results based on randomly generated instances show the effectiveness of the proposed technique.