Evolution of Maintenance Processes in Industry 4.0

2020 ◽  
pp. 49-69
Author(s):  
Adithya Thaduri ◽  
Stephen Mayowa Famurewa
Keyword(s):  
Decision Making ◽  
Conceptual Model ◽  
Asset Management ◽  
Industry 4.0 ◽  
Intelligent Systems ◽  
Operational Efficiency ◽  
Physical Asset ◽  
Set Up ◽  
Maintenance Process ◽  
Reduced Risk

Several industries are looking for smart methods to increase their production throughput and operational efficiency at the lowest cost, reduced risk, and reduced spending of resources considering demands from stakeholders, governments, and competitors. To achieve this, industries are looking for possible solutions to the above problems by adopting emerging technologies. A foremost concept that is setting the pace and direction for many sectors and services is Industry 4.0. The focus is on augmenting machines and infrastructure with wireless connectivity, sensors, and intelligent systems to monitor, visualize, and communicate incidences between different entities for decision making. An aspect of physical asset management that has been enormously influenced by the new industrial set-up is the maintenance process. This chapter highlights the issues and challenges of Industry 4.0 from maintenance process viewpoint according to EN 60300-3-14. Further, a conceptual model on how maintenance process can be integrated into Industrial 4.0 architecture is proposed to enhance its value.

Evolution of Maintenance Processes in Industry 4.0

2021 ◽  
pp. 76-96
Author(s):  
Adithya Thaduri ◽  
Stephen Mayowa Famurewa
Keyword(s):  
Decision Making ◽  
Conceptual Model ◽  
Asset Management ◽  
Industry 4.0 ◽  
Intelligent Systems ◽  
Operational Efficiency ◽  
Physical Asset ◽  
Set Up ◽  
Maintenance Process ◽  
Reduced Risk

Several industries are looking for smart methods to increase their production throughput and operational efficiency at the lowest cost, reduced risk, and reduced spending of resources considering demands from stakeholders, governments, and competitors. To achieve this, industries are looking for possible solutions to the above problems by adopting emerging technologies. A foremost concept that is setting the pace and direction for many sectors and services is Industry 4.0. The focus is on augmenting machines and infrastructure with wireless connectivity, sensors, and intelligent systems to monitor, visualize, and communicate incidences between different entities for decision making. An aspect of physical asset management that has been enormously influenced by the new industrial set-up is the maintenance process. This chapter highlights the issues and challenges of Industry 4.0 from maintenance process viewpoint according to EN 60300-3-14. Further, a conceptual model on how maintenance process can be integrated into Industrial 4.0 architecture is proposed to enhance its value.

IT Management Agility in Large Organizations

2019 ◽  
pp. 172-229
Keyword(s):  
Decision Making ◽  
Asset Management ◽  
Service Management ◽  
It Governance ◽  
Large Company ◽  
It Service ◽  
Management Processes ◽  
Agile Approach ◽  
Set Up ◽  
Digital Enterprise

A successful IT service and asset management need to be efficient and agile to help transform from a traditional into a digital enterprise. In this chapter, the authors propose a global and practical strategic framework to improve ITSM service management processes with the additions of two drivers: agility management based on DevOps and security management based on SecOps. The proposed framework will affect all aspects of user productivity DSI oriented and implement an agile approach in the heart of the management of all these aspects. They will study a case of application of the proposed framework on a large company and the gain made on the strategic level and decision making. The authors propose to measure the maturity of the ITSM of the organization and set up their benchmark to improve IT governance through the proposed ITSM framework.

Factors influencing Industry 4.0 adoption

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sabai Khin ◽  
Daisy Mui Hung Kee
Keyword(s):  
Decision Making ◽  
Conceptual Model ◽  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Content Type ◽  
Advantages And Disadvantages ◽  
Factors Influencing ◽  
Use Of Technology ◽  
Market Opportunities ◽  
The Right

PurposeThe digital transformation towards Industry 4.0 (I4.0) has become imperative for manufacturers, as it makes them more flexible, agile and responsive to customers. This study aims to identify the factors influencing the manufacturing firms’ decision to adopt I4.0 and develop a triadic conceptual model that explains this phenomenon.Design/methodology/approachThis study used a qualitative exploratory study design based on multiple case studies (n = 15) from the manufacturing industry in Malaysia by conducting face-to-face interviews. The data were analysed using NVivo. The conceptual model was developed based on grounded theory and deductive thematic analysis.FindingsResults demonstrate that driving, facilitating and impeding factors play influential roles in a firms’ decision-making to adopt I4.0. The major driving factors identified are expected benefits, market opportunities, labour problem, customer requirements, competition and quality image. Furthermore, resources, skills and support are identified as facilitating factors and getting the right people, lack of funding, lack of knowledge, technical challenges, training the operators and changing the mindset of operators to accept new digital technologies are identified as impeding factors.Research limitations/implicationsDue to its qualitative design and limited sample size, the findings of this study need to be supplemented by quantitative studies for enhanced generalizability of the proposed model.Practical implicationsKnowledge of the I4.0 decision factors identified would help manufacturers in their decision to invest in I4.0, as they can be applied to balancing advantages and disadvantages, understanding benefits, identifying required skills and support and which challenges to expect. For policymakers, our findings identify important aspects of the ecosystem in need of improvement and how manufacturers can be motivated to adopt I4.0.Originality/valueThis study lays the theoretical groundwork for an alternative approach for conceptualizing I4.0 adoption beyond UTAUT (Unified Theory of Acceptance and Use of Technology). Integrating positive and negative factors enriches the understanding of decision-making factors for I4.0 adoption.

Green sourcing in the era of industry 4.0: towards green and digitalized competitive advantages

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alireza Fallahpour ◽  
Morteza Yazdani ◽  
Ahmed Mohammed ◽  
Kuan Yew Wong
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Industry 4.0 ◽  
Supplier Selection ◽  
Research Work ◽  
Operational Efficiency ◽  
Chain Management ◽  
Content Type ◽  
The Way

PurposeIn the last decade, sustainable sourcing decision has gained tremendous attention due to the increasing governmental restrictions and public attentiveness. This decision involves diverse sets of classical and environmental parameters, which are originated from a complex, ambiguous and inconsistent decision-making environment. Arguably, supply chain management is fronting the next industrial revolution, which is named industry 4.0, due to the fast advance of digitalization. Considering the latter's rapid growth, current supplier selection models are, or it will, inefficient to assign the level of priority of each supplier among a set of suppliers, and therefore, more advanced models merging “recipes” of sustainability and industry 4.0 ingenuities are required. Yet, no research work found towards a digitalized, along with sustainability's target, sourcing.Design/methodology/approachA new framework for green and digitalized sourcing is developed. Thereafter, a hybrid decision-making approach is developed that utilizes (1) fuzzy preference programming (FPP) to decide the importance of one supplier attribute over another and (2) multi-objective optimization on the basis of ratio analysis (MOORA) to prioritize suppliers based on fuzzy performance rating. The proposed approach is implemented in consultation with the procurement department of a food processing company willing to develop a greener supply chain in the era of industry 4.0.FindingsThe proposed approach is capable to recognize the most important evaluation criteria, explain the ambiguity of experts' expressions and having better discrimination power to assess suppliers on operational efficiency and environmental and digitalization criteria, and henceforth enhances the quality of the sourcing process. Sensitivity analysis is performed to help managers for model approval. Moreover, this work presents the first attempt towards green and digitalized supplier selection. It paves the way towards further development in the modelling and optimization of sourcing in the era of industry 4.0.Originality/valueCompetitive supply chain management needs efficient purchasing and production activities since they represent its core, and this arises the necessity for a strategic adaptation and alignment with the requirement of industry 4.0. The latter implies alterations in the avenue firms operate and shape their activities and processes. In the context of supplier selection, this would involve the way supplier assessed and selected. This work is originally initiated based on a joint collaboration with a food company. A hybrid decision-making approach is proposed to evaluate and select suppliers considering operational efficiency, environmental criteria and digitalization initiatives towards digitalized and green supplier selection (DG-SS). To this end, supply chain management in the era of sustainability and digitalization are discussed.

scholarly journals Improving Decision-Making Grid based on interdependence among failures with a case study in the steel industry

2019 ◽  
Vol 31 (2) ◽  
pp. 167-182 ◽  
Author(s):  
Arash Shahin ◽  
Ashraf Labib ◽  
Soroosh Emami ◽  
Mahdi Karbasian
Keyword(s):  
Decision Making ◽  
Asset Management ◽  
Block Diagram ◽  
Fault Tree Analysis ◽  
Content Type ◽  
Steel Making ◽  
Physical Asset ◽  
Mean Time ◽  
Continuous Casting Plant

Purpose Decision-Making Grid (DMG) is used for determining maintenance tactics and is associated with the reliability and risk management of assets. In this grid, decision making is performed based on two indicators of Mean Time to Repair (MTTR) and frequency of failures. The purpose of this paper is to improve DMG by recognizing interdependence among failures. Design/methodology/approach Fault Tree Analysis and Reliability Block Diagram have been applied for improving DMG. The proposed approach has been examined on eight equipment of the steel making and continuous casting plant of Mobarakeh Steel Company. Findings Findings indicate different positions of equipment in the cells of the new grid compared to the basic grid. Research limitations/implications DMG is limited to two criteria of frequency of failures and MTTR values. In both basic and new DMGs, cost analysis has not been performed. The application of the proposed approach will help the reliability/maintenance engineers/analysts/managers to allocate more suitable maintenance tactics to equipment. This, in turn, will enhance the equipment life cycle and availability as the main objectives of physical asset management. Originality/value A major limitation of basic DMG is that the determined tactic based on these two indicators might not be an appropriate solution in all conditions, particularly when failures are interdependent. This has been resolved in this paper.

scholarly journals Evaluating Industry 4.0 Technology Application in SMEs: Using a Hybrid MCDM Approach

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 414
Author(s):  
Shih-Chia Chang ◽  
Hsu-Hwa Chang ◽  
Ming-Tsang Lu
Keyword(s):  
Decision Making ◽  
Industry 4.0 ◽  
Multiple Criteria Decision Making ◽  
Analytic Network Process ◽  
Performance Estimation ◽  
Influential Factor ◽  
Technology Application ◽  
Network Process ◽  
Toe Framework ◽  
Set Up

Evaluating Industry 4.0 technology application in small and medium-sized enterprises (SMEs) is an issue that requires a multi-criteria strategy comprising quantitative and qualitative elements. The purpose of this study is to integrate performance estimation of Industry 4.0 technology application using the technology–organization–environment (TOE) framework. Relating TOE to Industry 4.0 technology application evaluation is more multifaceted than other methods and it requires comprehensive analysis. In this study, we applied a multiple-criteria decision-making (MCDM) approach to develop a model which integrates MCDM to perform an assessment that prioritizes the influence weights of Industry 4.0 technology application to SMEs’ factors. Firstly, we carried out a review of the literature and the TOE framework was selected to generate nine elements, along with three aspects used to measure Industry 4.0 technology application in SMEs. Secondly, the approach of the decision-making trial and evaluation laboratory (DEMATEL) was set up using an influence network relations digraph (INRD). The DEMATEL-based analytic network process (DANP) was used to indicate the influence weights linking the above aspects and elements. Lastly, the modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique applied influence weights to assess the aspects/elements in the gaps identified and to investigate how to reduce the gaps so as to estimate the application of Industry 4.0 technology by SMEs. The results show that the technology aspect is the most influential factor.

THE CONCEPT OF AUTONOMOUS SYSTEMS IN INDUSTRY 4.0

2019 ◽  
Vol 12 (1) ◽  
pp. 77-87
Author(s):  
György Kovács ◽  
Rabab Benotsmane ◽  
László Dudás
Keyword(s):  
Industry 4.0 ◽  
Intelligent Systems ◽  
Autonomous Systems ◽  
Essential Element ◽  
Industrial Sector ◽  
Life Cycles ◽  
Multi Agent Systems ◽  
New Paradigm ◽  
Intelligent Machines ◽  
Digital Network

Recent tendencies – such as the life-cycles of products are shorter while consumers require more complex and more unique final products – poses many challenges to the production. The industrial sector is going through a paradigm shift. The traditional centrally controlled production processes will be replaced by decentralized control, which is built on the self-regulating ability of intelligent machines, products and workpieces that communicate with each other continuously. This new paradigm known as Industry 4.0. This conception is the introduction of digital network-linked intelligent systems, in which machines and products will communicate to one another in order to establish smart factories in which self-regulating production will be established. In this article, at first the essence, main goals and basic elements of Industry 4.0 conception is described. After it the autonomous systems are introduced which are based on multi agent systems. These systems include the collaborating robots via artificial intelligence which is an essential element of Industry 4.0.

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