An application of grey based decision making approach for the selection of manufacturing system

2014 ◽  
Vol 4 (3) ◽  
pp. 447-462 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
G. Anand
Keyword(s):  
Decision Making ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Strategic Decision ◽  
Decision Matrix ◽  
Content Type ◽  
Manufacturing Organization ◽  
Decision Making Model ◽  
Selection Of

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.

Selection of lean manufacturing systems using the PROMETHEE

2008 ◽  
Vol 3 (1) ◽  
pp. 40-70 ◽  
Author(s):  
G. Anand ◽  
Rambabu Kodali
Keyword(s):  
Decision Making ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Strategic Decision ◽  
Computer Integrated Manufacturing ◽  
Preference Ranking ◽  
Manufacturing Strategy ◽  
Manufacturing Companies ◽  
Content Type

PurposeIn recent years, many manufacturing companies are attempting to implement lean manufacturing systems (LMS) as an effective manufacturing strategy to survive in a highly competitive market. Such a process of selecting a suitable manufacturing system is highly complex and strategic in nature. The paper aims to how companies make a strategic decision of selecting LMS as part of their manufacturing strategy, and on what basis such strategic decisions are made by the managers.Design/methodology/approachA case study of a small‐ and medium‐sized enterprise is presented, in which the managers are contemplating on implementing either computer integrated manufacturing systems (CIMS) or LMS. To supplement the decision‐making process, a multi‐criteria decision making (MCDM) model, namely, the preference ranking organisation method for enrichment evaluations (PROMETHEE) is used to analyse how it will impact the stakeholders of the organisation, and the benefits gained.FindingsAn extensive analysis of PROMETHEE model revealed that LMS was the best for the given circumstances of the case.Research limitations/implicationsThe same problem can be extended by incorporating the constraints (such as financial, technical, social) of the organisation by utilising an extended version of PROMETHEE called the PROMETHEE V. Since, a single case study approach has been utilised, the findings cannot be generalized for any other industry.Practical limitations/implicationsThe methodology of PROMETHEE and its algorithm has been demonstrated in a detailed way and it is believed that it will be useful for managers to apply such MCDM tools to supplement their decision‐making efforts.Originality/valueAccording to the authors’ knowledge there is no paper in the literature, which discusses the application of PROMETHEE in making a strategic decision of implementing LMS as a part of an organisation's manufacturing strategy.

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

2018 ◽  
Vol 25 (1) ◽  
pp. 280-296 ◽  
Author(s):  
Ram Prakash ◽  
Sandeep Singhal ◽  
Ashish Agarwal
Keyword(s):  
Decision Making ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Research Work ◽  
Sustainable Growth ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Manufacturing Company ◽  
Selection Of

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.

scholarly journals Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL

2018 ◽  
Vol 25 (5) ◽  
pp. 1528-1547 ◽  
Author(s):  
Anil Kumar ◽  
Amit Pal ◽  
Ashwani Vohra ◽  
Sachin Gupta ◽  
Suryakant Manchanda ◽  
...  
Keyword(s):  
Decision Making ◽  
Automobile Industry ◽  
Supplier Selection ◽  
Selection Process ◽  
Strategic Decision ◽  
Extensive Literature ◽  
Content Type ◽  
Fuzzy Delphi ◽  
Selection For ◽  
Decision Making Model

Purpose Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry. Design/methodology/approach To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.

Integrated methodology for industrial facilities management and design based on FCA and lean manufacturing principles

Facilities ◽  
2020 ◽  
Vol 38 (7/8) ◽  
pp. 523-538 ◽  
Author(s):  
Diego Guillen ◽  
Diego Gomez ◽  
Ingrid Hernandez ◽  
Daniela Charris ◽  
Juan Gonzalez ◽  
...  
Keyword(s):  
Decision Making ◽  
Continuous Improvement ◽  
Lean Manufacturing ◽  
Primary Objective ◽  
Strategic Decision ◽  
Systematic Evaluation ◽  
Internal Quality ◽  
Strategic Decision Making ◽  
Production Plant ◽  
Content Type

Purpose The purpose of this paper is to provide a comprehensive methodology and a case study about the successful integration of FCA with continuous improvement tools for strategic decision-making processes. Reliable knowledge of the condition of tangible assets and their ability to fulfill their target activities over time are required for an assertive strategical decision process. Facility condition assessment (FCA) is a recognized methodology that allows the systematic evaluation of this performance. For those companies whose primary objective is the production of goods, decisions associated with improvements on the productive system or re-adaptation of existing assets may also require the implementation of alternative methodologies, with a direct impact on the indicators of the company and therefore on the FCA. Design/methodology/approach This study presents a methodology for the integration of FCA and lean manufacturing (LM) as a tool in strategic decision-making process that involves the integration of continuous improvement processes or significant changes in the production process, in which the condition of the installation impacts decisively the productivity of the system. Findings The results of the implementation on an insecticide and herbicide production plant indicate an increase of 33 per cent in the capacity of the formulation process and over 20 per cent reduction in the internal quality claims associated with the packaging system. Practical implications Those methodological stages are applicable to facilities in which the FCA shows the need for significant reconditioning of assets, the need to increase the efficiency and/or the production capacity. This methodology integrates elements of continuous improvement and redesign of production systems. Originality/value The original value of this paper is oriented to the capacity to integrate different FCA and LM tools through the company indicators of productivity key performance indicators and, in addition, of a comprehensive illustration based on a study case.

Profit-Oriented Decision-Making Model of Manufacturing Systems

2011 ◽  
Vol 201-203 ◽  
pp. 378-382
Author(s):  
Meng Qi Li ◽  
Dong Ying Li
Keyword(s):  
Decision Making ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Objective Evaluation ◽  
Sales Volume ◽  
Evaluation Mode ◽  
Decision Making Model ◽  
Model Environment ◽  
Single Objective ◽  
Evaluation Complexity

Multi-objective evaluation mode is used in manufacturing system all the time, and this would lead to evaluation complexity and subjectivity when objective number increases. Hence, enterprise profit- oriented single-objective is proposed and created. Then three profit structure elements: sales volume, price and cost as well as their influencing factors are analyzed, and "profit-elements(-properties)-scheme" is created. With this model, environment properties scheme is decided to verify its validity and operation simplicity.

Assessment of a reconfigurable manufacturing system

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Durga Prasad ◽  
S.C. Jayswal
Keyword(s):  
Lean Manufacturing ◽  
Design Methodology ◽  
Manufacturing System ◽  
Product Family ◽  
Part Family ◽  
Content Type ◽  
Space Cost ◽  
Utilization Cost ◽  
Selection Of

Purpose The purpose of this paper is to develop the methodology which can facilitate the concept of reconfiguration in the manufacturing system. Design/methodology/approach Design methodology includes the calculation of similarity matrix, formation of part family, and selection of part family. ALC algorithm has been used for part family formation and three criteria have been considered for the selection of part family. These criteria are reconfiguration effort, under-utilization cost, and floor space cost. AHP has been used to calculate the weights of criteria and reference ideal method has been used for the selection of alternatives. Findings In the manufacturing system, machines should be grouped on the basis of reconfiguration cost. When the time period is less, light machines and Group 1 machines are added and removed. In the case study, the concept of reconfiguration is useful for families (A, B, C, D). Machines can be reused by adding/removing some modules of machines. The concept of reconfiguration becomes more useful when it is implemented with lean manufacturing. Lean manufacturing techniques Jidoka and Poka-yoke are used to increase the diagnosability of the system. Practical implications Industrial case study has been considered. Social implications Market competition is increasing rapidly and it increases the demand and variety of products, due to which manufacturing enterprises are forced to adapt a manufacturing system which can adjust its capacity and functionality quickly at low cost. To reconfigure manufacturing system from one product/product family to another product/product family, changes can be done in hardware and/or software components in response to sudden changes in the market or in regulatory requirements. Originality/value An integrated approach for reconfiguration has been proposed considering the industrial application. It includes weighted Jaccard function, ALCA, AHP, RIM. The methodology for calculation of reconfiguration effort, under-utilization cost, and floor space cost has been presented for industrial case.

A maturity assessment model for manufacturing systems

2018 ◽  
Vol 29 (5) ◽  
pp. 746-767 ◽  
Author(s):  
Jorge A. Vivares ◽  
William Sarache ◽  
Jorge E. Hurtado
Keyword(s):  
Decision Making ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Assessment Model ◽  
Maturity Index ◽  
Manufacturing Companies ◽  
Maturity Level ◽  
Content Type ◽  
Maturity Assessment ◽  
Support Decision Making

PurposeAssessment of manufacturing systems provides a baseline for manufacturing strategy (MS) formulation. The purpose of this paper is to develop and propose a maturity assessment model for manufacturing systems (MAMMS). The MAMMS provides a maturity index, in order to establish manufacturing system performance on five possible levels: preinfantile, infantile, industry average, adult, and world class manufacturing.Design/methodology/approachThree main steps were taken: MAMMS design; maturity-level assessment in two companies; and MAMMS validation. Based on an action-research process, several research tools, such as surveys, expert panels, and immersion in two manufacturing companies, were used.FindingsBy integrating 79 variables into a maturity index, the maturity level for two manufacturing companies was obtained. Considering three main components (competitive priorities, manufacturing levers, and manufacturing’s strategic role), the analyzed companies showed a performance at the average industry level. According to participants, the MAMMS is a valuable tool to support decision making in MS.Practical implicationsEmpirical evidence supports the relevance of the proposed MAMMS and its practical usefulness. In particular, the maturity index identifies strengths and weaknesses in the manufacturing system, providing a baseline from which to deploy MS.Originality/valueThe literature review shows a lack of contributions regarding maturity models, particularly, the non-existence of maturity assessment models for manufacturing systems. The proposed MAMMS is a valuable tool to support decision making in MS. Also, this paper contributes to understanding the action-research paradigm, for further research in operations management.

Selection of project delivery approach with unascertained model

Kybernetes ◽  
2015 ◽  
Vol 44 (2) ◽  
pp. 238-252 ◽  
Author(s):  
Huimin Li ◽  
Keli Qin ◽  
Peng Li
Keyword(s):  
Decision Making ◽  
Delivery System ◽  
Information Entropy ◽  
Construction Project ◽  
Project Delivery ◽  
Content Type ◽  
Decision Making Model ◽  
Uncertainty Environment ◽  
Delivery Approach ◽  
Selection Of

Purpose – The construction project is implemented under uncertainty environment, and the product of construction is very complex. Selecting a project delivery system/approach is a critical task, which determines the project schedule, quality and investment objectives. The purpose of this paper is to propose a decision-making model for the selection of project delivery system which is based on information entropy and unascertained measure model. Design/methodology/approach – A decision-making model based on information entropy and unascertained set is employed to select project delivery approach. In order to overcome the subjective evaluations from the experts, the theory of “entropy weight” is applied to modify the experts’ subjective weight. The multi-attribute unascertained measure decision making is fitted to deal with the uncertainty information for selection of project delivery system. Findings – The proposed methodology is more comprehensive compared with the previous work, especially in the uncertainty environment. Research limitations/implications – There is some further work that should be considered, such as how to deal with the imprecise and subjective information given by the experts; how to determine the weight of the experts’; finding a set of importance factors influencing the selection of a delivery system is a complex task to further research. Practical implications – The proposed method can help the construction owner to select a most fitted project delivery system of a construction project. Originality/value – A new approach to select project delivery approach is proposed based on information entropy and unascertained set.

scholarly journals Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Literature Review ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Production Networks ◽  
Production Logistics ◽  
Time Production

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

Sign in / Sign up

Export Citation Format

Share Document