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Managing Innovation and Sustainable Development in the Era of Industry 4.0

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 55270

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Special Issue Editors

Prof. Dr. Piera Centobelli

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Guest Editor

Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy
Interests: operations management; logistics and supply chain management; decision support systems; knowledge management; technology management; Industry 4.0; environmental sustainability; circular economy; triple bottom line; manufacturing; production planning and control; digital transformation; digital factory; big data and analytics; blockchain; complex industries
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Wael Elgaraihy

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Co-Guest Editor

College of Applied Studies and Community Service, IMAM ABDULRAHMAN BIN FAISAL, Dammam, Saudi Arabia
Interests: operations management; supply chain performance measurement; practice-based supply chain sustainability; logistics and supply chain management; closed-loop supply chain; financial, social, and environmental sustainability; circular economy; manufacturing; production planning and control; blockchain

Special Issue Information

Dear Colleagues,

The Industry 4.0 paradigm is revolutionizing service and manufacturing industries, exploiting the adoption of innovative digital technologies like Internet of Things (IoT), cyber-physical systems (CPS), artificial intelligence (AI), big data and analytics, cloud computing, robotics, augmented reality, and additive manufacturing. All companies and supply chain functions (e.g., purchasing, manufacturing, and logistics) are facing this revolution, and the digital innovations are offering new internationalization opportunities for individual firms and supply chains. In this evolving scenario, supply firms are going to see radical changes, forcing them to improve their standard in product/process design. Key factors in this transition are: high flexibility, dynamic and circular market, increasing customization, high-quality products, flexible batches, sustainable practices, and short product life cycles.

At the same time, the shift towards sustainable supply chain management and development is emerging. The triple bottom line (TBL) expands the traditional framework aimed to improve social and environmental performance in addition to financial ones. The pursuit of the TBL in terms of environmental, financial, and social strategies requires the transformation of the entire supply chain and its operations. Previous studies have shown the importance of considering the three sustainable perspectives simultaneously for the role they play in pursuing sustainable development in both developing and developed countries. With these premises, the main aim of this Special Issue is to investigate the role of the Industry 4.0 paradigm and technologies for the achievement of sustainable development, TBL, circular economy, internationalization, and collaboration opportunities.

Prof. Dr. Piera Centobelli
Prof. Dr. Wael Elgaraihy
Guest Editors

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Keywords

Industry 4.0
enabling technologies
Internet of Things (IoT)
cyber-physical systems (CPS)
artificial intelligence (AI)
big data and analytics
cloud computing
robotics
augmented reality
additive manufacturing
3D printing
manufacturing
circular economy
sustainability
sustainable processes
sustainable development goals
internationalization
triple bottom line
supply chain management

Published Papers (13 papers)

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Research

Jump to: Review

27 pages, 1822 KiB

Open AccessArticle

A Novel Multi-Criteria Sorting Model Based on AHP-Entropy Grey Clustering for Dealing with Uncertain Incoming Core Quality in Remanufacturing Systems

by Mohamad Imron Mustajib, Udisubakti Ciptomulyono and Nani Kurniati

Appl. Sci. 2021, 11(6), 2731; https://doi.org/10.3390/app11062731 - 18 Mar 2021

Cited by 10 | Viewed by 2028

Abstract

Remanufacturing is a key pillar of a circular economy and helps in recovering used products by extending their life cycle via remanufacturing them into new products. A vital aspect in a remanufacturing system is the quality assessment of incoming worn-out products (cores) prior to remanufacturing to ensure that non-conforming cores are discarded at an early stage in order to avoid unnecessary processing. Therefore, quality sorting plays an important role in core acquisition for remanufacturing systems when attempting to mitigate uncertain incoming core quality as an immediate solution. The main problem is that it is difficult to acquire the important information required to decide on the sorting of incoming cores, such as the core quality. The data are also commonly limited, not always available, or inaccurate. Grey systems are powerful methods in decision making when handling uncertainty with small data. In this paper, we consider the usefulness of grey systems for handling uncertain quality information for sorting incoming cores in a remanufacturing system. For this reason, we propose a multi-criteria quality sorting model based on an analytical hierarchy process (AHP)-entropy model that is coupled with grey clustering using possibility functions. The quality criteria for sorting the incoming cores are considered according to the technological, physical, and usage conditions. To demonstrate the practical contribution of this research, a case study of the quality sorting problem with a heavy-duty equipment remanufacturer is presented. The proposed model consistently classifies the quality of used hydraulic cylinders into two grey classes. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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18 pages, 1574 KiB

Open AccessArticle

The Selection of Strategic Alliance in IC Packaging and Testing Industry with DEA Resampling Comparative Evaluation

by Chia-Nan Wang, Yi-Chun Peng, Ming-Hsien Hsueh and Yen-Hui Wang

Appl. Sci. 2021, 11(1), 204; https://doi.org/10.3390/app11010204 - 28 Dec 2020

Cited by 3 | Viewed by 2652

Abstract

Merger and acquisition (M&A) cases and the speed of horizontal integration have increased rapidly in the integrated circuit (IC) packaging and testing industry. Therefore, cooperation with suitable strategic alliance partner is a vital success factor for enterprises. This study proposes a “comparative evaluation” model that searches out appropriate strategic alliances on the basis of the resampling model acquired via data envelopment analysis (DEA). The realistic public data of 20 companies was collected from 2015 to 2019 in the IC packaging and testing industry. The super slacks-based measure model was used to evaluate the performance before alliance in the period from 2015 to 2019. The resampling past–present–future model was used to forecast the performance in 2020–2024. Afterward, a future strategic alliance for comparative evaluation of efficiency was established. The results of the alliance were divided into the groups “ineffective” and “effective”. The results show that 11 companies in the “effective” group achieved both improvements and 8 companies in the “ineffective” group achieved only unilateral improvements. The comparison model describes the efficiency of both sides simultaneously, not only from the perspective of the target but also from the perspective of the partner company. The evaluation model proposed in the study enables enterprises to find suitable alliance partners. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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28 pages, 3559 KiB

Open AccessArticle

Motivations for the Use of IoT Solutions by Company Managers in the Digital Age: A Romanian Case

by Mirela Cătălina Tűrkeș, Sorinel Căpușneanu, Dan Ioan Topor, Adela Ioana Staraș, Mihaela Ștefan Hint and Laurentiu Florentin Stoenica

Appl. Sci. 2020, 10(19), 6905; https://doi.org/10.3390/app10196905 - 01 Oct 2020

Cited by 15 | Viewed by 4180

Abstract

The purpose of our study is to research and identify intrinsic and extrinsic motivations but also their impact on the behavioral intentions of using Internet of Things (IoT) solutions among company managers in Romania in the future. The research method used in the quantitative study was the sample survey, using the online questionnaire as a data collection tool. The questionnaire included a formalized set of 54 questions, being specially designed to generate a new structural model starting from the Unified Theory for Acceptance and Use of Technology (UTAUT) elements. A total of 416 respondents provided complete and useful answers for this research. The results of the study showed that the endogenous factor intrinsically motivated significantly and strongly affected the intention of managers to use IoT solutions in professional activity compared to the variable of extrinsic motivation whose action remains insignificant. At the same time, the effect of the intrinsic motivation variable was mediated by the significant influence of the endogenous extrinsic motivation factor. The implications of this study are multiple for both managers and researchers. The originality of this article lies in the empirical part of the research, which, by using a quantitative method based on the questionnaire, provides important information on the impact of the motivational spectrum on the acceptance and use of IoT solutions by managers in the next period to achieve new performance, both personal and professional. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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11 pages, 1109 KiB

Open AccessArticle

Factors in the Relationship between Maintenance Engineering and Knowledge Management

by Javier Cárcel-Carrasco, José-Antonio Cárcel-Carrasco and Elisa Peñalvo-López

Appl. Sci. 2020, 10(8), 2810; https://doi.org/10.3390/app10082810 - 18 Apr 2020

Cited by 10 | Viewed by 2606

Abstract

The mechanisms of transmission and management of knowledge are mostly created by maintenance and exploitation activities of large buildings and industrial facilities, but they are poorly studied due to the difficulty capturing themas they belong to tacit knowledge gained by the experience of the maintenance staff. These professionals are highly qualified and are accostumed to solving technical problems even under pressure. The loss of these professionals means losing also an important asset of the company. This article will tackle the importance of the factors that influence knowledge management (KM) in maintenance engineering and its barriers and facilitators. The research is carried out by qualitative investigation on maintenance staff of an industrial company. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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17 pages, 2517 KiB

Open AccessArticle

A Heuristic Solution Method for Multi-Depot Vehicle Routing-Based Waste Collection Problems

by Yanjun Shi, Lingling Lv, Fanyi Hu and Qiaomei Han

Appl. Sci. 2020, 10(7), 2403; https://doi.org/10.3390/app10072403 - 01 Apr 2020

Cited by 19 | Viewed by 4314

Abstract

This paper addresses waste collection problems in which urban household and solid waste are brought from waste collection points to waste disposal plants. The collection of waste from the collection points herein is modeled as a multi-depot vehicle routing problem (MDVRP), aiming at minimizing the total transportation distance. In this study, we propose a heuristic solution method to address this problem. In this method, we firstly assign waste collection points to waste disposal plants according to the nearest distance, then each plant solves the single-vehicle routing problem (VRP) respectively, assigning customers to vehicles and planning the order in which customers are visited by vehicles. In the latter step, we propose the sector combination optimization (SCO) algorithm to generate multiple initial solutions, and then these initial solutions are improved using the merge-head and drop-tail (MHDT) strategy. After a certain number of iterations, the optimal solution in the last generation is reported. Computational experiments on benchmark instances showed that the initial solutions obtained by the sector combination optimization algorithm were more abundant and better than other iterative algorithms using only one solution for initialization, and the solutions with distance gap were obtained using the merge-head and drop-tail strategy in a lower CPU time compared to the Tabu search algorithm. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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14 pages, 707 KiB

Open AccessArticle

Evaluation of Smart Alarm Systems for Industry 4.0 Technologies

by Che-Wei Chang

Appl. Sci. 2020, 10(6), 2022; https://doi.org/10.3390/app10062022 - 16 Mar 2020

Cited by 8 | Viewed by 3257

Abstract

Traditionally, the footwear industry is labor intensive, and cost control is key to ensuring shoe companies can be competitive. The development of Industry 4.0 concepts, used in high-tech industries and blockchain production information systems, enables the creation of smart factories with online alarm management systems, to improve manufacturing efficiency and reduce human resource requirements. In this paper, the performances of the causal association assessment model and the technique for order preference by similarity to the ideal solution (TOPSIS) model in evaluating large data blockchain technologies and quality online real-time early warning systems for production and raw material supplier management are compared, to increase the intelligence of production and to manage product traceability. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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13 pages, 25471 KiB

Open AccessArticle

Modelling a Safety Management System Using System Dynamics at the Bhopal Incident

by Mario Di Nardo, Marianna Madonna, Teresa Murino and Francesco Castagna

Appl. Sci. 2020, 10(3), 903; https://doi.org/10.3390/app10030903 - 30 Jan 2020

Cited by 28 | Viewed by 6291

Abstract

In a safety management system (SMS), risk management plays a key role for the prevention of accidents. This study aims to propose a safety management model by using a system dynamics approach applied to the Bhopal incident. The model proposed in this paper discusses the relationships among the main causes that have contributed to the occurrence of the incident studied, such as broken safety devices, inadequate personnel experience, operator decisions, manager production strategy, policy decision, as deduced from the relevant literature about the Bhopal incident dynamics. The simulation and the results clarify how to manage the key factors to make the plant safe. Moreover, we want to underline how these key modern aspects of safety could be enhanced by using the enabling technologies of industry 4.0. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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18 pages, 2570 KiB

Open AccessArticle

Evaluating Centralized and Heterarchical Control of Smart Manufacturing Systems in the Era of Industry 4.0

by Anna Rosaria Boccella, Piera Centobelli, Roberto Cerchione, Teresa Murino and Ralph Riedel

Appl. Sci. 2020, 10(3), 755; https://doi.org/10.3390/app10030755 - 21 Jan 2020

Cited by 46 | Viewed by 3851

Abstract

In light of the Fourth Industrial Revolution, the concepts of flexibility and re-configurability of manufacturing systems and the evolution of their control architectures are becoming increasingly important. The development of Cyber Physical Systems (CPS) and their flexibility and integrated capabilities have paved the way to the transition from centralized control to heterarchical (decentralized) control architectures. In this paper, a comparison between centralized and heterarchical control architectures in a virtual learning environment is presented. The control architectures of the assembly station and the materials handling system of modern manufacturing systems have been conceptualized and tested under different working conditions. The results show that centralized control is the best solution only for deterministic and predictable scenarios, which are very far from reality, whereas, in case of failures, a more flexible control is preferable. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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16 pages, 3007 KiB

Open AccessArticle

Intelligent Monitoring of Data Center Physical Infrastructure

by Vojko Matko, Barbara Brezovec and Miro Milanovič

Appl. Sci. 2019, 9(23), 4998; https://doi.org/10.3390/app9234998 - 20 Nov 2019

Cited by 8 | Viewed by 9663

Abstract

This paper presents a new intelligent monitoring and event management method for data center physical infrastructure based on multilayer node event processing. The priorities of highly classified data centers are not only the maintenance of the highest level of reliability and availability of the operation, but also fast, specific event identification and energy consumption monitoring, which altogether improve the level of energy efficiency. The new method, using a tree node for each device, improves information about the events in a specific node. Its major advantage is that in the case of a large number of nodes, it considerably reduces the number of identified events (alarms/alerts) that might be the main cause. Fast event processing lowers data center physical infrastructure operating costs, improving at the same time the level of energy efficiency. The experimental results show that the use of tree nodes significantly reduces the number of unexpected events, the time needed for the main event identification, and the maintenance response time to events. By using event entities processing, multilayer nodes have a significant impact on the efficient operation of data center physical infrastructure. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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23 pages, 4504 KiB

Open AccessArticle

Semantic Data Management for a Virtual Factory Collaborative Environment

by Artem A. Nazarenko, Joao Sarraipa, Luis M. Camarinha-Matos, Oscar Garcia and Ricardo Jardim-Goncalves

Appl. Sci. 2019, 9(22), 4936; https://doi.org/10.3390/app9224936 - 16 Nov 2019

Cited by 11 | Viewed by 3255

Abstract

Recent developments in the area of cyber-physical systems (CPSs) and Internet of Things (IoT) are among the drivers for the emergence of the Industry 4.0 concept, setting new requirements for the architecture, technology, and design approaches of modern industrial systems. Industry 4.0 assumes a higher level of intelligence, and thus autonomy of the systems and subsystems, and a larger focus on the analysis of gathered data for further utilization. The Virtual Factory Open Operating System (vf-OS) project is intended to respond to some of these key challenges, in particular for the smart factory application domain. Complementarily, data and knowledge storage and processing are also in the scope of vf-OS. This article introduces the semantic management component of vf-OS, which aims to analyze the interrelations among stored entities, as well as to define the closeness among them to generate meaningful suggestions, which can be later used by other subsystems or operators in a user-friendly way. The semantic managing system makes use of non relational approaches, namely a graph database, which enables data to be represented as graphs for further semantic querying. The developed prototype and an illustrative application case are also presented. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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18 pages, 6818 KiB

Open AccessArticle

Generating Transparency in the Worldwide Use of the Terminology Industry 4.0

by Lars Nolting, Jan Priesmann, Christina Kockel, Georg Rödler, Tobias Brauweiler, Ines Hauer, Martin Robinius and Aaron Praktiknjo

Appl. Sci. 2019, 9(21), 4659; https://doi.org/10.3390/app9214659 - 01 Nov 2019

Cited by 9 | Viewed by 3274

Abstract

In 2011, the concept of Industry 4.0 was introduced and later adopted by the German government, paving the way for a new industrial revolution in Germany. The high significance of this topic is reflected by the large number of corresponding publications. Additionally, the regional focus of research is widespread on a global level and often differs even at a national level. This paper generates transparency regarding the adoption of the concept of Industry 4.0 by analyzing the locations of main contributors within the research field on an international, European, and German-national level. Further, it examines the regionally different foci concerning the concept of Industry 4.0. Having identified four main aspects linked to Industry 4.0 within a pre-study, a quantitative literature research was conducted based on over 800 published papers. The results were further visualized with QGIS. Looking at the results, it can be concluded that the German research community is virtually the only user of the term Industry 4.0, while other institutions seem to link their research to other related concepts. On a German level, the majority of the analyzed studies originate from Southern and Western Germany. North Rhine-Westphalia and the Aachen/Jülich region, in particular, represent main contributors. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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20 pages, 6106 KiB

Open AccessArticle

A Route Planner Using a Delegate Multi-Agent System for a Modular Manufacturing Line: Proof of Concept

by Lukáš Ďurica, Michal Gregor, Vladimír Vavrík, Martin Marschall, Patrik Grznár and Štefan Mozol

Appl. Sci. 2019, 9(21), 4515; https://doi.org/10.3390/app9214515 - 24 Oct 2019

Cited by 14 | Viewed by 2982

Abstract

Route planning in a multi-agent system (MAS) is still a complex task, especially if there is need for a continuous, decentralized planner of the routes for physical agents in a dynamic environment. It is a planner of this kind that is required in the application the article considers: the transportation of parts at a modular manufacturing line. Such a planner has to meet several difficult requirements, regarding the physical, time-constrained dynamic environment, live-locks and deadlocks, delayed agents, and last needs to minimize the travel time and the total distance traveled. The article proposes an approach using a delegate multi-agent system (D-MAS) in order to meet these requirements. The approach was verified using virtual reality so as to provide a better understanding of the planner’s issues. Several coordination rules were proposed and implemented. As a further verification, the proof-of-concept solution was compared to a non-reservation planner. It was shown, that as the number of agents increases, the approach, including the reservations, outperformed its competitor. Various recommendations for the implementation of the planner were formulated. It was concluded that the performance of the planner is sufficient for its future use. The main objective of article was proof-of-concept and determining the functionality of a prototype based on MAS that was in compliance with a modular manufacturing line developed by us. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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Review

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29 pages, 846 KiB

Open AccessReview

Assessing SMEs’ Internationalisation Strategies in Action

by Francesco Castagna, Piera Centobelli, Roberto Cerchione, Eugenio Oropallo, Shashi and Serena Strazzullo

Appl. Sci. 2020, 10(14), 4743; https://doi.org/10.3390/app10144743 - 09 Jul 2020

Cited by 5 | Viewed by 5993

Abstract

In this paper, a structured review was conducted to investigate the internationalisation process of small and medium enterprises (SMEs) to define barriers and enablers and identify research gaps in this relevant field. Data were collected from two databases of scientific peer-reviewed articles (i.e., Scopus and Web of Science). After the selection process, 161 papers focusing on SMEs’ internalisation were analysed using both descriptive and content analysis. The analysis of the results highlights that SMEs’ internalisation is a growing research field, but different research gaps remain to be filled. These gaps concern barriers, impact on performance, models, and theories related to the different phases of the internationalisation process (e.g., start-up, early entrance, international growth). The future research directions identified interesting suggestions and guidelines for future researchers in the field of SMEs internationalisation. Full article

(This article belongs to the Special Issue Managing Innovation and Sustainable Development in the Era of Industry 4.0)

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