Setting-up material handling network in manufacturing systems using graph theory

2018 ◽  
Vol 15 (1) ◽  
pp. 58-67 ◽  
Author(s):  
Shashank Gupta ◽  
Piyush Gupta

Purpose Material handling (MH) is an important facility in any manufacturing system. It facilitates the transport of in-process material from one workstation (WS) to another. MH devices do imply incurring capital costs and, therefore, minimizing their deployment without compromising on smooth material flow will ensure savings in addition to the optimal use of productive shop floor space and, avoid space cluttering. The purpose of this paper is to evaluate the minimal network that connects all the WSs, therefore ensuring economic and safe manufacturing operations. Design/methodology/approach Graph theoretical approach and Prim’s algorithm for minimal spanning tree is used to evaluate the minimal span of the MH devices. The algorithm is initialized by translating the graph of WSs into a distance matrix to evaluate the minimal MH network. Findings The minimal length of the MH devices is evaluated for a typical case study. Research limitations/implications The step-by step methodology explained in the manuscript acts as a good guide for practicing operational managers. The shortcoming of the methodology is that, it presumes the use of modular MH devices that will need to be reconfigured based on dynamic changes to the manufacturing system. Practical implications The methodology is explained in detail to enable the practicing managers to use it for designing their MH networks in any manufacturing system. Originality/value There is no evidence to indicate the use of minimal spanning tree algorithm for design of MH networks in a manufacturing system. This paper attempts to fill this gap.

2014 ◽  
Vol 25 (6) ◽  
pp. 891-915 ◽  
Author(s):  
Ibrahim H. Garbie

Purpose – The purpose of this paper is to propose a “Reconfiguration Methodology” in manufacturing systems that they can become more economically sustainable and can operate efficiency and effectively. This methodology will allow customized flexibility and capacity not only in producing a variety of products (parts) and with changing market demands, but also in changing and reengineering the system itself. Design/methodology/approach – Reconfigurable manufacturing system (RMS) is a philosophy or strategy which was introduced during the last decade to achieve agility in manufacturing systems. Until now, the RMS philosophy was based changing activities such routing, planning, programming of machines, controlling, scheduling, and physical layout or materials handling system. But the RMS concept can be based on the needed reconfiguration level (NRL), operational status of production systems, and new circumstances (NC). The NRL measure is based on the agility level of the manufacturing systems which is based on technology, people, management, and manufacturing strategies. The components of the manufacturing system design (MSD) consist of production system design, plant layout system, and material handling system. Operational status of production systems includes machine capability (flexibility) and capacity (reliability), production volume or demand, and material handling equipment in addition to the plant layout. The NC are also consisting of new product, developing the existing ones, and changing in demand. Findings – Reconfiguration manufacturing systems from one period to another period is highly desired and is considered as a novel manufacturing philosophy and/or strategy toward creating new sustainable manufacturing systems. A new reconfiguration methodology for the manufacturing systems will be analyzed and proposed. Two Case studies will be introduced. Originality/value – The suggestion of a new methodology of reconfiguration including the NRL (configurability index) and the operational status of manufacturing systems with respect to any circumstance is highly considered. The reconfiguration methodology also provides a framework for sustainability in the manufacturing area which mainly focussed on manufacturing systems design.


2018 ◽  
Vol 38 (12) ◽  
pp. 2313-2343 ◽  
Author(s):  
Daniel R. Eyers ◽  
Andrew T. Potter ◽  
Jonathan Gosling ◽  
Mohamed M. Naim

Purpose Flexibility is a fundamental performance objective for manufacturing operations, allowing them to respond to changing requirements in uncertain and competitive global markets. Additive manufacturing machines are often described as “flexible,” but there is no detailed understanding of such flexibility in an operations management context. The purpose of this paper is to examine flexibility from a manufacturing systems perspective, demonstrating the different competencies that can be achieved and the factors that can inhibit these in commercial practice. Design/methodology/approach This study extends existing flexibility theory in the context of an industrial additive manufacturing system through an investigation of 12 case studies, covering a range of sectors, product volumes, and technologies. Drawing upon multiple sources, this research takes a manufacturing systems perspective that recognizes the multitude of different resources that, together with individual industrial additive manufacturing machines, contribute to the satisfaction of demand. Findings The results show that the manufacturing system can achieve seven distinct internal flexibility competencies. This ability was shown to enable six out of seven external flexibility capabilities identified in the literature. Through a categorical assessment the extent to which each competency can be achieved is identified, supported by a detailed explanation of the enablers and inhibitors of flexibility for industrial additive manufacturing systems. Originality/value Additive manufacturing is widely expected to make an important contribution to future manufacturing, yet relevant management research is scant and the flexibility term is often ambiguously used. This research contributes the first detailed examination of flexibility for industrial additive manufacturing systems.


2019 ◽  
Vol 26 (2) ◽  
pp. 498-529 ◽  
Author(s):  
Rahul Sindhwani ◽  
Varinder Kumar Mittal ◽  
Punj Lata Singh ◽  
Ankur Aggarwal ◽  
Nishant Gautam

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.


2014 ◽  
Vol 4 (3) ◽  
pp. 447-462 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
G. Anand

Purpose – In the current customer-driven market, the manufacturers have to be highly responsive and flexible to deliver a variety of products. Hence, to meet this dynamic and uncertain market changes, the production system, which enables the manufacturing of such variety of products should be able to meet such diverse, dynamic changes. Hence, selecting a suitable manufacturing system is a key strategic decision for today's manufacturing organization, which needs to survive in these uncertain market conditions. Hence, the purpose of this paper is to present a decision-making model for selecting the best manufacturing system and also discuss the criteria on the basis of which the management can select the same. Design/methodology/approach – A case of small- and medium-sized company is presented, in which the management is deciding to establish a most suitable manufacturing system. To supplement this, a suitable multi-criteria decision-making model (MCDM), the grey approach is used to analyze manufacturing system alternatives based on various decision criteria to arrive a comparative ranking. Findings – An extensive analysis of grey-based decision-making model described grey decision matrix, grey normalized decision matrix, grey weighted normalized decision matrix and grey possibility degrees for three alternatives revealed that lean manufacturing systems was found to be the most suitable manufacturing system among three alternatives for a given case. Research limitations/implications – The same study can be extended by including sub-criteria with main criteria for selection of manufacturing system by utilizing two MCDM techniques such as AHP or ANP with Grey approach. Practical implications – The Grey approach has been discussed in a detailed way and it will be useful for the managers to use this approach as a tool for solving similar type of decision-making problems in their organizations in the future. Originality/value – Although, the problem of selecting a suitable manufacturing system is often addressed both in practice and research, very few reports are available in the literature of Grey-based decision models that demonstrated its application for selecting a suitable manufacturing systems.


Author(s):  
Wesley Ellgass ◽  
Nathan Holt ◽  
Hector Saldana-Lemus ◽  
Julian Richmond ◽  
Ali Vatankhah Barenji ◽  
...  

With the developments and applications of the advanced information technologies such as cloud computing, internet of thing, artificial intelligence and virtual reality, industry 4.0 and smart manufacturing era are coming. In this respect, one of the specific challenges is to achieve a connection of physical resources on the shop floor with virtual resources, for real-time response, real time process optimization, and simulation, which is merged by big data problem. In this respect, Digital Twins (DT) concept is introduced as a key technology, which includes physical resources, virtual resources, service system, and digital twin data. DT considers current condition of physical resource and prediction of future events to make a responsive decision. However, due to the complexity of building a digital equivalent in virtual space to its physical counterpart, very little applications have been developed with this purpose, especially in the industrial manufacturing area. Therefore, the types of data and technology required to build the DT for a manufacturing system are presented in this work, trying to develop a framework of DT based manufacturing system, which is supported by the virtual reality for virtualization of physical resources.


2017 ◽  
Vol 28 (5) ◽  
pp. 655-685 ◽  
Author(s):  
Christen Rose-Anderssen ◽  
James Baldwin ◽  
Keith Ridgway

Purpose The purpose of this paper is to critically evaluate the state of the art of applications of organisational systematics and manufacturing cladistics in terms of strengths and weaknesses and introduce new generic cladistic and hierarchical classifications of discrete manufacturing systems. These classifications are the basis for a practical web-based expert system and diagnostic benchmarking tool. Design/methodology/approach There were two stages for the research methods, with eight re-iterative steps: one for theory building, using secondary and observational data, producing conceptual classifications; the second stage for theory testing and theory development, using quantitative data from 153 companies and 510 manufacturing systems, producing the final factual cladogram. Evolutionary relationships between 53 candidate manufacturing systems, using 13 characters with 84 states, are hypothesised and presented diagrammatically. The manufacturing systems are also organised in a hierarchical classification with 13 genera, 6 families and 3 orders under one class of discrete manufacturing. Findings This work addressed several weaknesses of current manufacturing cladistic classifications which include the lack of an explicit out-group comparison, limited conceptual cladogram development, limited use of characters and that previous classifications are specific to sectors. In order to correct these limitations, the paper first expands on previous work by producing a more generic manufacturing system classification. Second, it describes a novel web-based expert system for the practical application of the discrete manufacturing system. Practical implications The classifications form the basis for a practical web-based expert system and diagnostic benchmarking tool, but also have a novel use in an educational context as it simplifies and relationally organises extant manufacturing system knowledge. Originality/value The research employed a novel re-iterative methodology for both theory building, using observational data, producing the conceptual classification, and through theory testing developing the final factual cladogram that forms the basis for the practical web-based expert system and diagnostic tool.


2018 ◽  
Vol 25 (1) ◽  
pp. 280-296 ◽  
Author(s):  
Ram Prakash ◽  
Sandeep Singhal ◽  
Ashish Agarwal

Purpose The 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/approach In 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. Findings Manufacturing 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/implications The 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 implications The 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/value The 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.


2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.


2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.


2018 ◽  
Vol 25 (4) ◽  
pp. 1171-1193 ◽  
Author(s):  
Raman Kumar ◽  
Harwinder Singh

Purpose The purpose of this paper is to explore the success factors for the assessment of manufacturing system output. Design/methodology/approach Exploratory factor analysis and second-order confirmatory factor analysis were used to analyze data and test hypotheses, respectively. A total of 36 observed variables were transformed into nine success factors, namely role of management (ROM), technical strength, employee strength, organizational strength (OS), resources (RS), production system, market research, effective planning, and research and development (RD). Findings The finding indicates that only four success factors, namely ROM, RS, OS, and RD, are positively related to all four outputs. Moreover, all nine success factors are positively associated with profit. Research limitations/implications The outcomes of the present work provide meaningful implications for researchers and practitioners as well. Originality/value Earlier studies have laid focus on single output only in the manufacturing system. In the present study, an effort has been made to focus on four output dimensions, namely final product, customer relationship, reputation, and profit, which are further strengthened by incorporating the concept of performance in manufacturing systems.


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