Industrial Paradigm Research Articles

Algorithm for Designing Reconfigurable Equipment to Enable Industry 4.0 and Circular Economy-Driven Manufacturing Systems

In the paradigm of industry 4.0, manufacturing enterprises need a high level of agility to adapt fast and with low costs to small batches of diversified products. They also need to reduce the environmental impact and adopt the paradigm of the circular economy. In the configuration space defined by this duality, manufacturing systems must embed a high level of reconfigurability at the level of their equipment. Finding the most appropriate concept of each reconfigurable equipment that composes an eco-smart manufacturing system is challenging because every system is unique in the context of an enterprise’s business model and technological focus. To reduce the entropy and to minimize the loss function in the design process of reconfigurable equipment, an evolutionary algorithm is proposed in this paper. It combines the particle swarm optimization (PSO) method with the theory of inventive problem-solving (TRIZ) to systematically guide the creative potential of design engineers towards the definition of the optimal concept over equipment’s lifecycle: what and when you need, no more, no less. The algorithm reduces the number of iterations in designing the optimal solution. An example for configuration design of a reconfigurable machine tool with adjustable functionality is included to demonstrate the effectiveness of the proposed algorithm.

Performance effects of digital technology adoption and product & service innovation – A process-industry perspective

European manufacturing companies face increasing pressure to adopt digitalization technologies discussed in the emerging paradigm of Industry 4.0. On the other hand, innovation capabilities both in terms of introducing new products and new services are of outmost importance to gain competitive advantage. Technology adoption and firm innovativeness are often interrelated, but this relation is not well understood, and in particular, the way in which digital technology adoption, product and service innovation, and competitive advantage are related to process industries has not yet been investigated. This paper develops and operationalizes a conceptual framework for product and service innovation, thereby incorporating digital technology adoption. Through an exploratory study, using quantitative data from the European Manufacturing Survey (EMS)-2015, we analyze data from 747 cases in the process industries from D, NL, A, CH, and DK. Our main findings show that companies with higher levels of digital technology implementation (breadth and depth) can introduce more radical product and service innovations. Companies with both radical innovations and service innovation make significantly greater use of their implemented technologies’ potential. Radical product innovation also yields higher returns on sales, but contrary to our assumptions, service innovation in process industries does not. We find that, in the low-tech sectors, digital technologies are used to generate product and services innovations which then translate into higher performance. In contrast, in the high-tech sectors, digital technologies have a direct impact on performance and are thus rather accustomed to realizing the efficiency gains not primarily used for innovation.

The Emergence of New Business and Operating Models under the Industrial Digital Paradigm. Industrial Internet of Things, Platforms, and Artificial Intelligence/Machine Learning

The Emergence of New Business and Operating Models under the Industrial Digital Paradigm. Industrial Internet of Things, Platforms, and Artificial Intelligence/Machine Learning

THE EFFECT OF THE CONSUMER DECISION-MAKING PROCESS ON THE PERCEIVED VALUE TOWARD SLOW FASHION

Slow fashion designates a new paradigm in the clothing industry that promotes the importance of fashion goods realized with natural and durable products, empowering consumers to use the purchased clothes for a longer time, decreasing, in this case, the environmental and societal impact of fashion pieces. Even if it designates the opposite of fast fashion production, the slow fashion notoriety is not remarkably high among consumers. This study proposed to examine the effect of the consumers' decision-making process on the noticed value toward slow fashion. In this regard, we considered multiple decision-making constructs and tested their impact on consumers’ perceived value toward slow fashion. Also, we examined if there are discrepancies in the perceived value toward slow fashion based on gender. A survey was designed and administrated in Romania to a sample of 330 consumers aged between 18-25. We applied to the collected data exploratory analysis to identify the distribution of manifest variables into factors, followed by confirmatory factor analysis to test the performance of the obtained factors. Finally, we tested the proposed hypotheses using the structural equation model procedure. Were identified seven dimensions that compose the decision-making process of the consumers, namely, recreational shopping, perfectionism, brand knowledge, over choice confusion, fashion awareness, impulsive buying, and brand loyalty. Also, were found three dimensions that constitute the consumers' perceived value toward slow fashion, namely, emotional, social, and financial dimensions. The results showed that over choice confusion exhibits a positive effect on the emotional and financial value; fashion awareness manifests a positive effect on the social value, while brand loyalty manifests a positive impact on the financial value. In the case of gender impact on the emotional value, it was identified that, if a respondent is a female, the influence is positive and statistically significant.

The Role of Maintenance Operator in Industrial Manufacturing Systems: Research Topics and Trends

Maintenance contributes to gaining high business performance, guarantees system availability and reliability as well as safe and sustainable operations. Maintenance activity effectiveness depends on competences and the skills of operators whose performance strongly affects maintenance and production operations. The research field of human issues in industrial maintenance was deeply addressed in the literature; however, the current industrial paradigm, which focusses on the integration of new technologies in conventional manufacturing operations to support human performance, sheds light on new challenges for enterprises and opportunities for research in this field. While some literature reviews in the field of human errors and human factors are available, no study investigated the main topics, research trends and challenges related to the role of maintenance operators in manufacturing systems. This paper addresses the current state-of-the-art role of maintenance operators in manufacturing systems, providing an overview of the main studies. A systematic literature review was carried out to identify significant papers. Then, a topic modelling algorithm was used to detect the main topics of the selected papers to provide the research trends of the subject. The identified topics provided interesting research insights on the human role in industrial maintenance. Research trends and further research opportunities were defined.

Towards Machine Learning for Error Compensation in Additive Manufacturing

Additive Manufacturing (AM) of three-dimensional objects is now being progressively realised with its ad-hoc approach with minimal material wastage (lean manufacturing) being one of its benefit by default. It could also be considered as an evolutional paradigm in the manufacturing industry with its long list of application as of late. Artificial Intelligence is currently finding its usefulness in predictive modelling to provide intelligent, efficient, customisable, high-quality and sustainable-oriented production process. This paper presents a comprehensive survey on commonly used predictive models based on heuristic algorithms and discusses their applications toward making AM “smart”. This paper summarises AM’s current trend, future opportunity, gaps, and requirements together with recommendations for technology and research for inter-industry collaboration, educational training and technology transfer in the AI perspective in-line with the Industry 4.0 developmental process. Moreover, machine learning algorithms are presented for detecting product defects in the cyber-physical system of additive manufacturing. Based on reviews on various applications, printability with multi-indicators, reduction of design complexity threshold, acceleration of prefabrication, real-time control, enhancement of security and defect detection for customised designs are seen of as prospective opportunities for further research.

Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution

The rise of personalised and highly complex drug product profiles necessitates significant advancements in pharmaceutical manufacturing and distribution. Efforts to develop more agile, responsive, and reproducible manufacturing processes are being combined with the application of digital tools for seamless communication between process units, plants, and distribution nodes. In this paper, we discuss how novel therapeutics of high-specificity and sensitive nature are reshaping well-established paradigms in the pharmaceutical industry. We present an overview of recent research directions in pharmaceutical manufacturing and supply chain design and operations. We discuss topical challenges and opportunities related to small molecules and biologics, dividing the latter into patient- and non-specific. Lastly, we present the role of process systems engineering in generating decision-making tools to assist manufacturing and distribution strategies in the pharmaceutical sector and ultimately embrace the benefits of digitalised operations.

Equilibrial service composition model in Cloud manufacturing (ESCM) based on non-cooperative and cooperative game theory for healthcare service equipping.

Industry 4.0 is the digitalization of the manufacturing systems based on Information and Communication Technologies (ICT) for developing a manufacturing system to gain efficiency and improve productivity. Cloud Manufacturing (CM) is a paradigm of Industry 4.0. Cloud Manufacturing System (CMS) considers anything as a service. The end product is developed based on the service composition in the CMS according to consumers’ needs. Also, composite services are developed based on the interaction of MCS providers from different geographical locations. Therefore, the appropriate Manufacturing Cloud Service (MCS) composition is an important problem based on the real-world conditions in CMS. The game theory studies the mathematical model development based on interactions between MCS providers according to real-world conditions. This research develops an Equilibrial Service Composition Model in Cloud Manufacturing (ESCM) based on game theory. MCS providers and consumers get benefits mutually based on ESCM. MCS providers are players in the game. The payoff function is developed based on a profit function. Also, the game strategies are the levels of Quality of Service (QoS) based on consumers’ needs in ESCM. Firstly, the article develops a composite service based on a non-cooperative game. The Nash equilibrium point demonstrates the QoS value of composite service and the payoff value for the players. Secondly, the article develops a composite service based on a cooperative game. The players participate in coalitions to develop the composite service based on formal cooperation. The grand coalition demonstrates the QoS value of composite service and the payoff value for the players in the cooperative game. The research has compared the games’ results. The players’ payoff and the QoS value are better in the cooperative game than in the non-cooperative game. Therefore, the MCS providers and consumers are satisfied mutually in the cooperative game based on ESCM. Finally, the article has applied ESCM in a Healthcare Service to equip 24 hospitals in the best time.

PARADIGMATIC APPROACH TO SYSTEM MANAGEMENT IN THE HOSPITALITY INDUSTRY

Building a modern competitive economy requires intensification of management and investment activities on the basis of innovation. In the conditions of intensification of the process of Ukraine’s integration into the European community there is a need to change the guidelines and transformational factors of the hospitality industry. The manifestation of crisis trends in the field of tourism and hotel and restaurant business indicates the need for a systematic approach to the organization and regulation of this area. The problem of revising the old and creating a new system management paradigm in the hospitality industry comes to the fore. The development of management, as art and theory, has evolved. However, the change in management tasks at certain stages of development of economic relations indicates a change in perceptions and approaches to the organization and regulation of economic and production processes. Moreover, this is determined by the dynamics of change in all areas and spheres of socio-economic, cultural, health and other forms of social activity. Depending on their importance, views on management changed at different stages, which manifested itself in the formation of relevant conceptual positions and different management paradigms and was reflected in the emergence of different scientific schools, such as “scientific management”, “classical”, “human relations”, quantitative approach ”,“ behavioral sciences ”,“ production activities ”, etc. Features of the current stage of development of public relations, the need for a strategic vision of the prospects of technological innovation necessitate a new approach to management, substantiation of new theoretical and practical principles of technological modernization of management systems in all sectors of the hospitality industry. The article deals with the pragmatic direction of creating tools for system management of the hospitality industry, in particular the transition to a new system of views on the activities of enterprises from the standpoint of theoretical positions in systems’ theory, organizational theory, systematic and situational approaches and analysis, economic theory, social psychology, computer sciences, and computer technologies. The new model of system management involves the connection and consistent use of theoretical principles and tools for the functioning of the control system. It is established that the system management paradigm is a process of regulation and coordination of production and economic operations, which is based on the properties of the process as a complex system; subordination to the laws of the organizational theory; the availability of tools that would ensure the manifestation of the properties of the system and the implementation of the laws of organizational theory.

A Tale of Two Food Chains: The Duality of Practices on Well‐being

In this paper, we honor Stanford University Professor Hau Lee, who is a great inspiration and thought leader in the supply chain and operations management (SC&OM) field. Our discussion centers around one of the most challenging SC&OM problems—food production, distribution, and consumption from dirt to table. We advocate and link our notions of emergent regenerative, organic food value chains (ROFVC) with quadruple‐aim performance (QAP) that connects financial outcomes with ecological, human, and socioeconomic well‐being. To do so, we first overview the systemic problems underlying the conventional food supply chains (CFSC) that render them unsustainable in the long run. In contrast, we introduce salient distinctions between CFSC and the new paradigm of ROFVC that uphold QAP. We believe the ideas generated in this paper can move the food systems’ SC&OM design, implementation, and performance measurement from an efficiency‐oriented industrial paradigm of large‐scale, factory farming toward a more encompassing view of eco‐responsible practices. In CFSC, the many hidden costs are cumulative and have broad deleterious consequences; however, in ROFVC, pollution is shunned and “taxed,” and sustainability, as a public good, is rewarded by sequestering greenhouse gas (GHG) emissions and maintaining biodiversity, living soil, as well as clean air and water. We conclude with research, teaching, and policy agendas. We believe that the underlying principles here cut across sectors by fostering the introduction of regenerative business models that take a system's view in capturing QAP in their value chain strategy and execution.

Towards an information semantic interoperability in smart manufacturing systems: contributions, limitations and applications

ABSTRACT One of the paradigms of Industry 4.0 is the quick answer of companies over changes on customer’s necessities. This can only be achieved when an efficient vertical and horizontal integration occurs across manufacturing systems. However, thousands of heterogeneous information must be exchanged across the process and semantic interoperability obstacles are identified for an effective communication. This research aims to identify the main bibliographical references that deal with horizontal and vertical integration to support a semantic interoperable manufacturing system. Also, it is proposed a preliminary approach to support a semantic interoperable horizontal and vertical integration across Smart Manufacturing Systems. A total of 732 articles were found and applying exclusion criteria the number went down to 31. A classification based on the subjects that each article contained was applied resulting in seven main works for the research themes. According to the analysis of the main works, the preliminary architecture was proposed using the semantic web approach and the formal rules. Although this research does not evaluate the performance of the solution proposed, it was evident that this field has new perspectives on future research opportunities to cope with the semantic information interoperability in multiple integration levels of manufacturing systems.

A Systematic Literature Review on Data and Information Required for Circular Manufacturing Strategies Adoption

In the extant literature, circular economy (CE) is considered a driver for sustainable development of the manufacturing sector, being it an industrial paradigm aiming at regenerating resources. CE is transferred to manufacturing companies through the adoption of different Circular Manufacturing (CM) strategies (e.g., recycling, remanufacturing, etc.). Nowadays, manufacturers are struggling to implement these strategies to limit their resource consumption and pollution generation. To enable their adoption, the extant literature unveiled the importance to control along the entire value chain different types of resource flows (i.e., material, energy, and information). Nevertheless, while for material and energy management some advancements were achieved, information management and sharing remains one of the major barriers in adopting these strategies. The present work, through a systematic literature review, aims to identify the relevant information and data required to support the manufacturer’s decision process in adopting and managing the different CM strategies to pursue the transition towards CM. Furthermore, based on the results obtained, this research proposes a theoretical framework. It elucidates the four main areas to be managed by manufacturers in adopting CM strategies and it provides to the manufacturer an overview of what should be updated and upgraded inside the company to embrace CM strategies.

Sanitizable Access Control System for Secure Cloud Storage Against Malicious Data Publishers

Cloud computing is considered as one of the most prominent paradigms in the information technology industry, since it can significantly reduce the costs of hardware and software resources in computing infrastructure. This convenience has enabled corporations to efficiently use the cloud storage as a mechanism to share data among their employees. At the first sight, by merely storing the shared data as plaintext in the cloud storage and protect them using an appropriate access control would be a nice solution. This is assuming that the cloud is fully trusted for not leaking any information, which is impractical as the cloud is owned by a third party. Therefore, encryption is mandatory, and the shared data will need to be stored as a ciphertext using an appropriate access control. However, in practice, some of these employees may be malicious and may want to deviate from the required sharing policy. The existing protection in the literature has been explored to allow only legitimate recipients to decrypt the contents stored in the cloud storage, but unfortunately, <i>no existing work</i> deals with issues raised due to the presence of malicious data publishers. Malicious data publishers construct data following the given policy, but the ciphertexts can actually be decrypted by unauthorized users without valid keys, or simply, anyone else who is unauthorized. The impact of the involvement of malicious data publishers is detrimental, as it may damage intellectual properties from the corporations. Therefore, it remains an elusive research problem on how to enable a sound approach to resolve the issue when malicious data publishers are involved in the system, which is a very practical question. In this work, we present <i>a new direction of research</i> that can cope with the presence of malicious data publishers. We resolve the aforementioned problem by proposing the notion of Sanitizable Access Control System (SACS), which is designed for a secure cloud storage that can also resist against malicious data publishers. We define the threat model and its formal security model, as well as its design and scheme which is based on <inline-formula><tex-math notation="LaTeX">$q$</tex-math><alternatives><mml:math><mml:mi>q</mml:mi></mml:math><inline-graphic xlink:href="susilo-ieq1-3058132.gif"/></alternatives></inline-formula>-Parallel Bilinear Diffie-Hellman Exponent Assumption. We provide the security proof of our construction as well as its performance analysis. We believe that this work has opened a new area of research which has never been explored before, even though it is very practical. Therefore, this work will enhance the adoption of secure cloud storage in practice.

Mejoramiento del algoritmo ADR en una red de internet de las cosas LoRaWAN usando aprendizaje de máquina

espanolEl Internet de las Cosas es un paradigma habilitador de la Industria 4.0, donde sensores y actuadores se conectan a Internet. El protocolo LoRaWAN (Long Range Area Network) es uno de los mas empleados, y es usado para transmitir informacion a largas distancias con minimo consumo energetico. Este protocolo implementa el esquema Adaptative Data Rate para mejorar la energia consumida por nodo, que al ser evaluado a traves de simulaciones exhaustivas en Omnet++, ha exhibido posibilidades de mejora en el tiempo de convergencia. El presente trabajo muestra una propuesta para el mejoramiento del algoritmo ADR de tal forma que se optimice el consumo energetico en redes LoRaWAN. Dentro de la propuesta se comparan diferentes modelos parametricos y no parametricos. Los resultados indican que los metodos basados en Maquinas de Vectores de Soporte y en Redes Neuronales Artificiales presentan la mayor exactitud, con un porcentaje por encima del 90% en las estimaciones. EnglishThe Internet of Things (IoT) is an enabling paradigm for Industry 4.0, where sensors and actuators connect to the Internet. The protocol LoRaWAN (Long Range Area Network) is one of the most used in the IoT, and its primary objective is to transmit sensor information over long distances with minimal energy consumption. This protocol implements Adaptive Data Rate scheme to optimize the energy consumed per node, which, when evaluated through exhaustive simulations in Omnet ++, has exhibited opportunities for improvement in convergence time. The present work shows machine learning models based on parametric and non-parametric methods based on Support Vector Machines (SVM) and Artificial Neural Networks (ANN). The results indicate that the SVM and ANN methods have a success rate greater than 90% in the estimated parameters.

Industry 4.0: advanced digital solutions implemented on a close power loop test bench

The paradigm of Industry 4.0 allows to increase the efficiency and effectiveness of the production. Companies that will implement advanced solutions in production systems will increase their level of competitiveness and will be able reach high market shares. The present paper is focused on the development of advanced digital solutions to be implemented on a close power loop test bench designed to test high power transmissions for naval unit. In particular, the test configuration consists of a back-to-back connection between two identical mechanical reducers. Since the efficiency of these systems are very high, it is not necessary to use large electric motors, thus managing to contain the operating costs of the testing phase. The particular test bench allows to size the electric motor simply based on the dissipated power by the kinematic mechanisms. By means of suitable sensors installed on the test bench it is possible to extrapolate countless technical data. The implementation of Industry 4.0 enabling technologies allows to evaluate the increase in efficiency compared to traditional systems in terms of reduction of noise and vibrations, efficiency of lubrication, reduction of consumption, installation and maintenance cost of the entire system.

Integration between Lean, Six Sigma and Industry 4.0 technologies

In the present decade, the manufacturing scenario is changing from the mass production to customised production with the advent of Industry 4.0 (I4.0). It has been also observed from the recent literature that there is a significant paradigm shift in the manufacturing system towards smart manufacturing or Industry 4.0. This has happened due to the adoption of advanced information/digital system along with latest technologies in the organisations. Lean and Six Sigma are the productivity and quality improvement methodologies for elimination of wastes and process variations respectively. In this paper, an attempt has been made to explore the interrelation between Lean, Six Sigma and Industry 4.0. It highlights the synergies among the concepts and technologies between these three domains with their interdependencies. Industry 4.0 creates a right platform to bring ample manufacturing capabilities to the next top level. It is clear that Lean and Six Sigma are basically data driven technologies and the new industrial paradigm can provide the right amount of informative data to strengthen these quality improvement approaches. Proper implications of Industry 4.0 technologies can boost the effectiveness of these two quality improvement techniques. The interdependencies of Lean Six Sigma, artificial intelligence and big data are also elaborated.

Exploring trust and responsiveness as antecedents for intention to use FinTech services

FinTech is an emerging paradigm in financial services industry which is becoming the additional source of revenue generation not only for banking companies but also for telecommunication and retail companies. Despite the numerous benefits of FinTech, its acceptance with users is not as per the industry expectations. This can be attributed to various factors such as lack of trust or responsiveness in available FinTech services. The objective of our research is to explore the antecedents of intention to use namely, perceived usefulness, perceived ease of use (PEU), perceived trust and responsiveness. These factors were empirically assessed by survey of 439 FinTech users. Exploratory factor analysis was done to extract relevant factors. Structural equation modelling was done to examine model fit and hypotheses testing. The analysis shows that usefulness and ease of use have direct effect on intention to use. Trust and responsiveness have indirect effect on intention to use and is mediated by usefulness and ease of use.

An Agent-based Model for Resource Provisioning and Task Scheduling in Cloud Computing Using DRL

The Resource Provisioning (RP) and Task Scheduling (TS) issues has become an attractive paradigms in cloud industry, this is due to the increasing demand for the services provided by virtual machines that are structured by physical servers owned by the data centers of cloud service providers (CSPs). In this paper, we propose a new model based on multi-agent system for the RP and TS reducing the cost of energy using Deep Reinforcement Learning DRL. A Quantile Regression Deep Q Network (QR-DQN) algorithm generates an appropriate policy and the optimal long-term decisions. A set of experiments show the efficiency of our proposed scheduling approach and the performance of our task allocation method..

The role of insectculture in the modern paradigm of the food industry in the Republic of Tatarstan

The socio-economic, biotechnological and environmental aspects of the organization of production and construction of a plant for deep processing of insectoculture in the Republic of Tatarstan are considered. Strategic analysis reveals the development of insect oculture as a key factor in improving the efficiency of food processing enterprises, organizing recycling and improving the state of the environment. The main product of the enterprise is a protein substrate, it is a well-balanced additive in mixed feed for poultry and fish farming and can become a reliable basis for import substitution in feed production. The products of vital activity of insects is a unique bio – fertilizer containing the whole complex of biologically active substances needed in crop production. The innovative technology of obtaining products of deep processing of insects is favorable not only in terms of the development of socio-economic processes in the republic, but also will give a new impetus to the development of the chemical, cosmetic and pharmaceutical industries in the Republic of Tatarstan.

Towards “Design for Interoperability” in the context of Systems Engineering

In product development, early decisions made within the requirements specification and design phase have significant impact on overall functionality, quality and lifecycle cost of the product. In Systems Engineering, these oftentimes iterative design phases are steered by underlying development models, providing processes, guidelines and best practices. One family of guidelines are the “Design for X” (DfX) tools or principles. In the development of mechatronic systems e.g. production systems, traditionally the mechanical, electric and software domain are to be distinguished. Over time, driven by trends of digitalization, communication and interconnection of systems, the product innovation and thus the required development effort has been shifting from the mechanical domain towards the software domain. The question of system interoperability thereby is of a fundamental nature. This is especially relevant within the current paradigms of Industry 4.0 and the Digital Twin.To reflect the growing importance of interoperability (i.e. the ability of systems to purposefully interchange interpretable information) as a requirement for the product within the design phase of technical systems, this paper introduces “Design for Interoperability” (DfIOp) as a new DfX principle. First, this is motivated by the ever-growing importance of information technology for current and future products. Then, the main contribution of the paper is the combination of the state of the art in the research domains of DfX, interoperability, Systems Engineering and Industry 4.0. Consequently, DfIOp will be presented, including a systematization model as well as a first method for its implementation. Further contemplation on DfIOp shows, that it enables derivative principles such as “Design for Data Analytics” and “Design for Digital Twin”. In future research, the underlying models as well as methods of DfIOp are to be further detailed and integrated into the research context.