DECISION SUPPORT FOR A SUSTAINABLE PRODUCTION IN JOB SHOP MANUFACTURING SYSTEMS

10.6036/9917 ◽  
2021 ◽  
Vol 96 (5) ◽  
pp. 455-459
Author(s):  
MAHDI NADERI ◽  
ANTONIO FERNÁNDEZ ULLOA ◽  
JOSÉ ENRIQUE ARES GÓMEZ ◽  
GUSTAVO PELÁEZ LOURIDO
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Sustainable Production ◽  
Ease Of Use ◽  
Manufacturing Companies ◽  
Strategic Decisions ◽  
Production Environments

Despite the growing importance that is being given to the concepts of sustainability in many areas, not only in industry but also in the economy and public opinion in general, until now, most research has focused, practically, on the analysis of the concepts, but has not addressed, in a comprehensive way, its impact in decision making probably due to the complex relations of interdependence between its different aspects. In this context, MAPSAM (Methodology for the Assessment of Sustainability in Manufacturing Processes and Systems) was created to help the decision-making process, allowing a conscious and transparent assessment by administrators and managers at the different levels of the structure of companies and organisations. This article explains its development and application in a "job shop" type manufacturing system with an approach that allows the integration of economic, environmental and social criteria. MAPSAM is based on the use of various techniques and tools to quantify the importance of each aspect of sustainability and it has been applied in other production environments, being implemented in different systems, analysing their ease of use and evaluating their behaviour. The objective is to show how it helps to make operational, tactical and strategic decisions in the management on these type of manufacturing companies and, specifically, in this contribution we want to highlight its versatility and applicability, by validating it in a certain type of layout. With this new application, MAPSAM increases its possibilities as an innovative instrument that allows companies to make conscious and sustainable decisions in order to be more efficient, fair, supportive and respectful of the environment. Keywords: Manufacturing System, Simulation, Decision Support, Sustainable Production, Decision-Making

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.

Decision Making and Support Tools for Design of Machining Systems

2011 ◽  
pp. 155-164 ◽  
Author(s):  
A. Dolgui ◽  
O. Guschinskaya ◽  
N. Guschinsky ◽  
G. Levin
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Product Design ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Expert Knowledge ◽  
Main Idea ◽  
Software Tools ◽  
Design Stage ◽  
Software Environment

The design of manufacturing systems is a wide open area for development and application of decision making and decision support technologies. This domain is characterized by the necessity to combine the standard decision making methods, sophisticated operational research techniques, and some specific rules based on expert knowledge to take into account principal technological constraints and criteria. A promising trend in this area deals with the development of integrated software tools (Brown, 2004; Grieves, 2005; Stark, 2005). Their main idea consists in integrating product and manufacturing data into a common database. This enables product designers to consider the manufacturing processes constraints at the early product design stage. At the same time, all data of product design should be used directly for optimizing the corresponding manufacturing system. That is why the core of these software tools is a powerful extendable database, supported by a user friendly software environment. This database normally contains digital models of product and processes. In order to find an optimal manufacturing system configuration, a set of advanced decision making and decision support methods are used for data processing.

Decision Making and Support Tools for Design of Machining Systems

2011 ◽  
pp. 591-603
Author(s):  
A. Dolgui ◽  
O. Guschinskaya ◽  
N. Guschinsky ◽  
G. Levin
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Product Design ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Expert Knowledge ◽  
Main Idea ◽  
Software Tools ◽  
Design Stage ◽  
Software Environment

The design of manufacturing systems is a wide open area for development and application of decision making and decision support technologies. This domain is characterized by the necessity to combine the standard decision making methods, sophisticated operational research techniques, and some specific rules based on expert knowledge to take into account principal technological constraints and criteria. A promising trend in this area deals with the development of integrated software tools (Brown, 2004; Grieves, 2005; Stark, 2005). Their main idea consists in integrating product and manufacturing data into a common database. This enables product designers to consider the manufacturing processes constraints at the early product design stage. At the same time, all data of product design should be used directly for optimizing the corresponding manufacturing system. That is why the core of these software tools is a powerful extendable database, supported by a user friendly software environment. This database normally contains digital models of product and processes. In order to find an optimal manufacturing system configuration, a set of advanced decision making and decision support methods are used for data processing.

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.

scholarly journals Development of a Decision Support System Framework for Cultural Heritage Management

2021 ◽  
Vol 13 (13) ◽  
pp. 7070
Author(s):  
Eleonora Di Di Matteo ◽  
Paolo Roma ◽  
Santo Zafonte ◽  
Umberto Panniello ◽  
Lorenzo Abbate
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Cultural Heritage ◽  
Design Science ◽  
Demand Management ◽  
Science Research ◽  
Ease Of Use ◽  
Heritage Management ◽  
Space Management ◽  
Managerial Implications

Decision support systems (DSSs) have been traditionally identified as useful information technology tools in a variety of fields, including the context of cultural heritage. However, to the best of our knowledge, no prior study has developed a DSS framework that incorporates all the main decision areas simultaneously in the context of cultural heritage. We fill this gap by focusing on design-science research and specifically by developing a DSS framework whose features support all the main decision areas for the sustainable management of cultural assets in a comprehensive manner. The main decision-making areas considered in our study encompass demand management, segmentation and communication, pricing, space management, and services management. For these areas, we select appropriate decision-making supporting techniques and data management solutions. The development of our framework, in the form of a web-based system, results in an architectural solution that is able to satisfy critical requirements such as ease of use and response time. We present an application of the innovative DSS framework to a museum and discuss the main managerial implications and future improvements.

Similarity-Based Decision Support for Internet Enabled Supply-Web Interactions

1998 ◽  
Author(s):  
Raj Veeramani ◽  
Narayanan Viswanathan ◽  
Shailesh M. Joshi
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Manufacturing Industry ◽  
Job Shop ◽  
The Internet ◽  
Agent Based ◽  
New Approaches ◽  
Effective Decision ◽  
Use Of The Internet ◽  
Effective Decision Making

Abstract New approaches for decision making are emerging to support the use of the Internet for supply-web interactions in the manufacturing industry. In this paper, we discuss one such paradigm, namely similarity-based decision support. It recognizes that knowledge of similar experiences can support rapid and effective decision making in various forms of supply-web interactions. We illustrate this approach using two prototype systems, WebScout (an agent-based system for customer–supplier matchmaking in the job-shop machining industry context) and TOME (Treasury of Manufacturing Experiences — an Intranet application to aid manufacturability assessment in foundries).

scholarly journals The adoption of an indicator panel in educational management to decision-making support

2020 ◽  
Vol 8 (6) ◽  
pp. 266-290
Author(s):  
Miguel Fabrício Zamberlan ◽  
Carolina Yukari Veludo Watanabe
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Educational Institution ◽  
Paraconsistent Logic ◽  
Ease Of Use ◽  
Adoption Of Technology ◽  
Utaut Model ◽  
Use Of Technology

The use of technology to assist in the performance of daily activities and to carry out communication between individuals has become a necessary task in the face of technological advances. In the context of public institutions, the insertion of technology is also based on the possibilities of making the activities of this sector more efficient and better quality, in addition to allowing greater transparency and accessibility of information for society. For public managers, the information and communication technology tools allow for a more accurate assessment of the variables and possibilities involved in a decision-making process and, thus, to make better decisions in a sector whose main customer is society (users). Therefore, this paper aimed to analyze the use and acceptance of a decision support tool in a public educational institution called the Indicators Panel. For this, the Unified Theory of Acceptance and Use of Technology (UTAUT) was used, and the results were measured using the paraconsistent logic. The results indicate that it is possible to consider the use and acceptance of the decision support system in the public educational institution by reducing the propositions of the UTAUT Model in three factors: Usability, Performance, and Relationship. Regarding the UTAUT Model, it was found that the moderating variables of gender, age, and experience do not significantly influence the adoption of the decision support system. It is important to note that managers point the tool as very important for the development of their activities and emphasize that ease of use is one of the main points for the adoption of technology.

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 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.

And The World Came To See: New Manufacturing System Designs and Industrial Revolutions

2002 ◽  
Author(s):  
J. T. Black ◽  
David S. Cochran
Keyword(s):  
System Design ◽  
Systems Engineering ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Flow Shop ◽  
The World ◽  
Industrial Revolutions ◽  
New System

AND THE WORLD CAME TO SEE. When a new manufacturing system design (MSD) is developed by a company or a group of companies, the rest of the world comes to those factories to learn about the new system. In the last 200 years, three new factory designs have evolved, called the job shop, the flow shop and the lean shop. Each is based on a new system design — a functional design, a product flow design and a linked cell design. New factory designs lead to new industrial leaders and even new industrial revolutions (IR’s). Two appendixes are included: One outlines the implementation strategy for the lean shop and the other is a discussion of lean manufacturing from the viewpoint of K. Hitomi, Japanese professor of manufacturing systems engineering.

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