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Data has become a high-value commodity in manufacturing. There is a growing realisation that the data-driven applications could become strong differentiators of manufacturing enterprises. To guide the developments in digitisation, a widely accepted framework is needed. In the absence of the universal framework, the components making a digital enterprise are captured in an example framework that is introduced in the paper. The adoption of new technology and software solutions has increased complexity of manufacturing systems. In addition, new product introductions have become more frequent and the demand more variable. A digital space enables optimisation and simulation of decisions before their realisation in the physical space. Predictive modelling with its time dimension is a valuable actor in the digital space. Three challenges of predictive modelling such as model complexity, model interpretability, and model reuse are identified in this paper. The coverage of each challenge in the literature is illustrated with the recently published papers. The main aspects of these challenges and the synthesis of the developments in digital manufacturing are articulated in the form of eight observations that could guide the future research. [ABSTRACT FROM AUTHOR]

Product performance and process versatility are key characteristics of composites but there is a trade off with productivity and consistency. The capability of composites technologies is highly dependent on the choice of materials and processes, which are considerable. Using the more demanding case of load bearing structural components, this paper investigates how different processes can be selectively utilised to meet desired design and manufacturing conditions. Although there are automated processes developed for specific product, the relative extremes of low and high performance applications are compared for generally available low and high productivity processes. This provides the basis of supporting a selection methodology, which has wider applications beyond the immediate technologies. [Copyright &y& Elsevier]

This survey explores applications of explainable artificial intelligence in manufacturing and industrial cyber–physical systems. As technological advancements continue to integrate artificial intelligence into critical infrastructure and industrial processes, the necessity for clear and understandable intelligent models becomes crucial. Explainable artificial intelligence techniques play a pivotal role in enhancing the trustworthiness and reliability of intelligent systems applied to industrial systems, ensuring human operators can comprehend and validate the decisions made by these intelligent systems. This review paper begins by highlighting the imperative need for explainable artificial intelligence, and, subsequently, classifies explainable artificial intelligence techniques systematically. The paper then investigates diverse explainable artificial-intelligence-related works within a wide range of industrial applications, such as predictive maintenance, cyber-security, fault detection and diagnosis, process control, product development, inventory management, and product quality. The study contributes to a comprehensive understanding of the diverse strategies and methodologies employed in integrating explainable artificial intelligence within industrial contexts. [ABSTRACT FROM AUTHOR]

The three-dimensional (3D) product model has become a tool that has transitioned from a legacy instrument, used in design, to an emerging technology applied to production and assembly processes. As this evolution has occurred, the need has developed to understand the value of deploying the 3D product model beyond the design phase. This research answers the question and solves the problem, does electronic documentation inclusive of the 3D product model add to the production workers' ability to complete the production task? To answer this question, the methods used were that the research team tested how accurately and quickly a production and assembly team could build the product using interactive, electronic documentation, including the 3D product model, as a means to understand the design intent as opposed to printed bills of materials (BOMs) and two-dimensional (2D) paper drawings. The conclusions that can be drawn from this research are that the research found statistically significant improvements in the production throughput time (~10%), reductions in the direct labor hours per unit (~14%), and retained quality levels, when deploying electronic documentation, including the 3D product model, into the production and assembly processes. Through the deployment of the interactive 3D product model electronic documentation to the production floor, the organization also took a step towards creating a digital twin of the produced product and laid a foundation for the further adoption of Industry 4.0 practices. The novelty of the work and the areas where it goes beyond previous efforts in the literature concerns the current body of knowledge that does not demonstrate a repeatable methodology through which industry and other researchers can replicate the experiment on demonstrating economic value when deploying the 3D product model to production and assembly processes. In this paper, the authors aim to build on prior work to demonstrate a repeatable methodology for determining the economic value of 3D product model deployment in production and assembly processes through applied research. [ABSTRACT FROM AUTHOR]

In practical manufacturing systems, the job processing time usually varies with the performance change of manufacturing resources, among which the learning and deteriorating effects are typical characteristics. Due to the interests from both academic exploration and industrial innovation, the research on scheduling problems with these effects is abundant and diverse. However, some studied problems need to be strengthened in combination with realistic production scenarios. This paper provides a concise guide to scheduling problems with these effects, giving a comprehensive review and critical hints for future research. A novel classification scheme is designed based on four levels of different domains, i.e. effects, processing ways, processing time functions, and manufacturing environments. Based on this scheme, the scheduling problems are first distinguished into three categories: learning effects, deteriorating effects, and combined effects. In each category, models are then refined along three lines: general processing way, batch scheduling, and group scheduling. Combined with the attributes of actual processing time functions and manufacturing environments, the evolvement of related scheduling models and a critical analysis on the proposed algorithms are well analysed. Afterwards, the research gaps are revealed and the research directions are indicated from the perspectives of practical applications, time functions, and designed algorithms. [ABSTRACT FROM AUTHOR]

The evolution of knowledge acquisition and representation in manufacturing technologies is vital for translating complex manufacturing data into actionable insights and advancing a comprehensive knowledge framework. This framework is pivotal in driving innovation and efficiency in intelligent manufacturing. This review aggregates recent research on knowledge acquisition and representation within the manufacturing process, addressing existing challenges and mapping potential future developments. It includes an analysis of 123 papers that focus on harnessing advanced intelligent analytics to extract operationally relevant knowledge from the extensive datasets typical in manufacturing environments. The narrative then examines the methodologies for constructing models of knowledge in manufacturing processes and explores their applications in manufacturing principles, design, management, and decision-making. This paper highlights the limitations of current technologies and projects emerging research avenues in the acquisition and representation of process knowledge within intelligent manufacturing systems, with the objective of informing future technological breakthroughs. [ABSTRACT FROM AUTHOR]

Copyright of Strategy & Development Review is the property of Strategy & Development Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Industry 4.0 refers to the digital transformation in the manufacturing domain through new technology. Currently, it expands well beyond manufacturing, affecting many areas of life and posing implications for all types of business. This paper focuses on the relationships between Industry 4.0 and Healthcare which transitions to increased interconnectivity, automation and smart decision making. The integration context of Industry 4.0 into Healthcare is only partly understood. Little was done until now to consolidate what is known on the integration benefits and the challenges. This article reports results of a systematic mapping study that analysed 69 papers to extract knowledge about the concepts of Industry 4.0 and the emerging Healthcare 4.0., and the relationships between them. We found 10 different perspectives of Healthcare 4.0, ranging from strategic to tactical and operational levels. Next, our results show: (i) nine applications of Industry 4.0 in the Healthcare domain: Augmented Reality and Simulation, Autonomous Robotics, Cybersecurity, Big Data Analytics, Internet of Things, Cloud Computing, Additive Manufacturing and Systems Integration; and (ii) 10 benefits and nine challenges in Healthcare 4.0. The most frequently mentioned benefits are patients' diagnosis, monitoring, treatment, and financial benefits. The most researched challenges are data fragmentation, heterogeneity, complexity, and privacy. [ABSTRACT FROM AUTHOR]

Increasing customer demands and product diversity as well as emerging technologies and market trends, such as the establishment of new driveline technologies, like e-mobility or hydrogen, present challenges for manufacturing companies in the commercial vehicle industry. Consequently, companies must strengthen their focus to the aspect of flexibility within their manufacturing processes. This paper contributes to the state of the art in flexible manufacturing technologies research, which enables manufacturing companies to deal with these increasing flexibility requirements. Focussing on the area of final assembly the paper takes a holistic perspective and characterizes the readiness of automotive companies to be able to implement flexible manufacturing technologies. The system ecosystem and the process organization of automotive companies are examined with respect to the requirements of flexible manufacturing. Finally, gaps that hinder the implementation of flexible manufacturing technologies are identified and described, and possible solution concepts for the identified gaps are proposed. [ABSTRACT FROM AUTHOR]

Throughout history, bookbinding incorporated advancements in techniques, usage of a wide range of materials, and application of imaginative designs. Lacquered bindings are just one of several technical breakthroughs attributed to Persian artisans. They consist of a sophisticated structure of numerous layers. This study explores each layer and their materials and methods, including motifs used from the Safavid to Qajar periods. Moreover, various treatments used for each layer during manufacture as well as various methods for preparing paper pasteboards, including marqaš, ṭalāyi, tah ṭalāyi, zarak, dūdī, and abrī have been investigated through literature research and reconstruction. The intricate layer combinations used in Persian lacquered bindings cause several simultaneous chemical processes. Chemical, physical, and biological degradation are significantly influenced by raw materials and the original manufacturing process. Separation of layers, softening, yellowing and loss of transparency, cracking, hazing, and pigment as well as metal corrosion brought on by internal and external deterioration factors including light, temperature, and relative humidity will also be covered in this study. [ABSTRACT FROM AUTHOR]

Implementing quality tools and methods creates a basic foundation for innovations, sustainability, optimization, and competitiveness in the era of Industry 4.0 and Quality 4.0. This paper aimed to investigate the use of quality tools and methods in the 24 divisions of a mother manufacturing company without the influence of external factors such as geographical location (America, Africa, Asia, and Europe). It was important for the mother manufacturing company to implement a uniform process standard for innovation and performance. Research methods focused on using the Kanban card, Ishikawa diagram, affinity diagram, Flowchart, 5S, OPL, layout, and Pareto analysis. It was determined in this research that the synergy (combination) of quality tools and methods in divisions improves the process performance. This hypothesis was confirmed by the results of implementing quality tools in processes within divisions. A top result was the new innovative model of synergy of the quality tools and methods for divisions of the parent company thus filling a gap in the scientific field. This model created the basis for the uniform process standard in all divisions. The results brought improvements in the processes such as material input inspection, spare parts production, production process, and product packaging. This model could be a proactive instrument for process innovation. [ABSTRACT FROM AUTHOR]

This paper presents a pioneering systematic literature review (SLR) that scrutinizes the increasingly pivotal role of resilience in manufacturing strategy (MS), a perspective notably absents in previous literature. In the wake of disruptive events, our study provides an exhaustive analysis of resilience within MS, employing a meticulous multi-stage process encompassing article collection, critical evaluation, and both bibliometric and content analyses. Utilizing Atlas.ti © for an enhanced analytical depth, the study distinctly maps current trends and pinpoints previously unexplored gaps in this research area. Post-2020, a surge in academic focus on MS and resilience is evident, and our analysis brings forth critical research domains such as the formulation of theoretical resilience frameworks and the refinement of strategic resilience in manufacturing. The study accentuates the necessity of agility and responsiveness in manufacturing, emphasizing the integration of uncertainty into decision-making processes. It also highlights the instrumental role of technological innovation, particularly the adoption of Industry 4.0 (I4.0) technologies, in reinforcing resilience. Through a detailed content analysis, our research systematically categorizes findings into approaches to resilience, resilience components, and MS resilience. This provides a structured and comprehensive understanding of the subject, advocating for a multidisciplinary approach that amalgamates strategic management, advanced technologies, and insights into cultural and organizational dynamics. This holistic perspective is vital for shaping manufacturing systems that are resilient and adaptable in a volatile global context. As a foundational reference, this study marks a significant leap in research, setting the stage for future endeavors to develop robust, adaptable manufacturing practices. [ABSTRACT FROM AUTHOR]

The rapid changes in customer demand force manufacturers to develop new technologies for flexibility enhancement in the manufacturing system. Different kinds of literature are available to explain the issues in the Flexible manufacturing system (FMS) and different traditional techniques employed for solving such issues. However, several new techniques have emerged in the past 25 years and no literature reviews exist to differentiate such modern approaches from traditional ones. The core purpose of this review is to study and investigate different levels of techniques involved in the effective implementation of FMS. This paper serves with some reasonable investigation of flexible issues faced in manufacturing industries such as scheduling, machine loading, material handling, and decision-making stage. For each manufacturing issue, the emerged manufacturing techniques are described in this review. This will also help future researchers interested in doing their research work in the area of FMS. It provides information to develop the best model for solving issues of the observed FMS problem. This paper contains the details of issues related to flexibility in manufacturing sectors with its resolving techniques that are reviewed and symbolized between the years 2000 and 2021. [ABSTRACT FROM AUTHOR]

Purpose: Smart manufacturing is the prime gripper for the transformation and upgrading of the manufacturing industry. Smart manufacturing systems (SMSs) largely determine how smart manufacturing evolves in technical and organizational dimensions and how it realizes values in products, production or services. SMSs are growing rapidly and receiving tons of attention from academic research and industrial practice. However, the development of SMSs is still in its fancy, and many issues wait to be identified and solved, such as single point failures, low transparency and ineffective resource sharing. Blockchain, an emerging technology deriving from Bitcoin, is competent to aid SMSs to conquer troubles due to its decentralization, traceability, trackability, disintermediation, auditability and etc. The purpose of this paper is to investigate the blockchain applications in SMSs, seek out the challenges faced by blockchain-enabled SMSs (BSMSs) and provide referable research directions and ideas. Design/methodology/approach: A comprehensive literature review as a survey is conducted in this paper. The survey starts by introducing blockchain concepts, followed by the descriptions of a literature review method and the blockchain applications throughout the product life cycle in SMSs. Then, the key issues and challenges confronting BSMSs are discussed and some possible research directions are also proposed. It finally presents qualitative and quantitative descriptions of BSMSs, along with some conclusions and implications. Findings: The findings of this paper present a deep understanding about the current status and challenges of blockchain adoption in SMSs. Furthermore, this paper provides a brand new thinking for future research. Originality/value: This paper minutely analyzes the impacts that blockchain exerts on SMSs in view of the product life cycle, and proposes using the complexity science thinking to deal with BSMSs qualitatively and quantitatively, including tackling the current major problems BSMSs face. This research can serve as a foundation for future theoretical studies and enterprise practice. [ABSTRACT FROM AUTHOR]

This paper examines the effect of frontier academic research on technological development and the way institutional quality influences this impact. Using a dataset that covers 18 OECD countries over the 2003–2017 period, we find that frontier academic research exerts an important influence on total factor productivity. First, frontier academic research induces technological change by directly enhancing production processes and management methods. Second, frontier academic research stimulates industrial innovations, which in turn improves productivity. Regarding the moderating effect of institutional variables on these relationships, we find that positive moderation only exists for some, not all, of the institutional variables. In that case, a higher level of these variables is found to strengthen the way countries reap benefits from frontier academic research and industrial innovation. However, the moderation of institutions is much less clear with the process that turns frontier academic research into industrial innovations. [ABSTRACT FROM AUTHOR]

The recent trend of globalisation of the economy has been accelerated thanks to emerging new communication technologies. This forces some companies to be adapted to rapidly changing market requirements utilising a multi-factory production network. Job scheduling in such a distributed manufacturing system, is significantly complicated especially in the presence of dynamic events. Furthermore, production systems need to be flexible to timely react to the imposed changes. Hence, reconfigurable machine tools (RMTs) can be used as a resource for flexibility in manufacturing systems. This paper deals with a distributed job-shop rescheduling problem, in which the facilities benefit from reconfigurable machines. Firstly, the problem is mathematically formulated to minimise total weighted lateness in a static state. Then, the dynamic version is extent based on a designed conceptual framework of rescheduling module to update the current schedule. Since the problem is NP-hard, a self-adaptive hybrid equilibrium optimiser algorithm is proposed. The experiments show that the proposed EO algorithm is extremely efficient. Finally, a simulation-optimisation model is developed to evaluate the performance of the manufacturing system facing stochastic arriving jobs. The obtained results show that the production system can be very flexible relying on its distributed facilities and reconfigurable machines. [ABSTRACT FROM AUTHOR]

Copyright of LogForum is the property of LogForum and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Various industries around the world recognize the importance of achieving Net Zero Greenhouse Gases (GHG) emission by 2050. Industrial processes have been attributed to the increase in CO2 concentrations causing climate change. As the rate of emissions continues to increase, there becomes a pressing need to adopt new technologies that allow for a real shift towards emission reduction. In this paper, Carbon Capture (CC) technologies are explored and reviewed across various industries namely: cement, steel, ethanol and powerplants. A statistical representation of various CC implementations and facilities is presented with a supportive case study, including some evaluative discussions of energy demands, capture rates, and economic impacts of various technology adoptions. Moreover, the paper includes a comparative data analysis of various solvents and configurations used for carbon capture, to show their effectiveness in reducing CO2 and cost of implementation. The paper also discusses some crucial limitations and challenges of CC, including economic and technical aspects. However, with the success seen in CC applications across various industries, there remains scope for future work to address novel solvents, with reduced costs and minimum modifications to existing processes. A brief overview of life cycle assessment of carbon capture and storage is also presented. [ABSTRACT FROM AUTHOR]

China's carbon peak strategy constrains industry's carbon footprint, limiting the total amount of electricity production from coal burning, rendering electricity a relatively scarce resource and affecting manufacturing enterprises' production and operation activities. To address these circumstances, this paper applies a non-cooperative game model to describe the electricity resource distribution and product production process under enterprises' competitive state, proposing an optimal electricity distribution analysis framework for manufacturing enterprises. The results of optimal electricity distribution for six subindustries in the 'three innovations' manufacturing industries (referring to a collection of economic activities to establish new industries, new formats and new business models) are analysed to examine the difference in electricity consumption efficiency among industries. The electricity quota of each industrial chain significantly differs before and after redistribution;therefore, the industrial differences of optimal electricity distribution are further explored from the perspective of industrial chains, revealing the supply–demand relationship of upstream, middle and downstream enterprises. Finally, corresponding policy suggestions and directions for further research are presented. [ABSTRACT FROM AUTHOR]

Blockchain (BC) applications in supply chain management (SCM) have recently received extensive attention. It is important to synthesise the extant literature on the field to identify key research themes and navigate potential future directions. This study thus develops an efficient, scalable data-driven review approach that uses text mining and Latent Dirichlet Allocation (LDA)-based topic modelling for automatic content analysis of full-text documents. Our method overcomes the drawbacks of traditional systematic literature reviews using either manual coding or bibliographic analysis for article classifications, which are highly time-consuming and biased when dealing with large amounts of text. 108 papers published between 2017 and 2022 were analysed which identified 10 key research themes, including revenue management, sustainability, traceability, manufacturing system, scheduling in cloud manufacturing, healthcare SCM, anti-counterfeit system, logistics and transportation, system architecture development, and food & agriculture SC. Five future directions are then suggested, including (1) integration of BC and other emerging technologies for global and scalable SCM, (2) crypto-X applications in SCM, (3) BC-enabled closed-loop SCM, (4) the environmental and social impacts of BC-based SCM and (5) decentralised autonomous organisations in SCM. [ABSTRACT FROM AUTHOR]

This paper presents the results of studies in the field of polymer materials application for fabric modification. The aim of the study is to identify the most effective technique of deposition of Russian-made formulations of an acryl and urethane nature with pigment compositions in the processes of functional fabric production. The authors analyze the efficiency of three processing solutions: the technology of uniform dyeing with pigments consisting of coating the fabric surface with a pigment–polymer composition, the technology of obtaining "camouflage" fabrics based on a conceptually new approach to creating the IR-remission effect on printed fabrics, and the technology of creating a stable retro-reflective effect on a fabric through the use of polymers produced in Russia. The paper also shows the conceptual differences in the pigment distribution mechanisms in the fiber or in the polymer matrix depending on the technique of fabric coating. The cheapest and safest technique for the environment is the squeegee method of pigment application, which provides fabrics with both oil- and water-repellent properties. An innovative technology has been developed based on the squeegee method for achieving the IR-remission effect on fabrics with "camouflage" patterns. A series of physico–chemical tests (spectrophotometry, electron microscopy), as well as assessment of the consumer properties of the obtained textile materials confirmed the efficiency of using aqueous dispersions of acrylic polymers made in Russia for producing competitive functional fabrics. [ABSTRACT FROM AUTHOR]

This paper reviews the basic implications and policy orientation of the new development pattern and the impacts of constructing the new development pattern on the manufacturing transformation and upgrading, based on which the choice of manufacturing transformation and upgrading paths is further discussed under the new development pattern. This paper holds that the paths of manufacturing transformation and upgrading need to be adjusted and expanded under the conditions of constructing the new development pattern. The main ideas are as follows. Restructuring the manufacturing industry chain with the large domestic market as the main guide, creating the good environment conducive to independent innovation, coordinating the regional layout for the overall high-quality manufacturing development, optimizing the business environment and enhancing the vitality and driving force of the manufacturing's development, relying on the Belt and Road Initiative (BRI) for a higher level of international circulation. The theoretical bases for adjusting and expanding the paths of manufacturing transformation and upgrading are: embracing the new requirements with domestic circulation as the mainstay, the characteristics with the mutual reinforcement of domestic and international circulations, and promoting the manufacturing's high-quality development and the medium and high-speed growth. [ABSTRACT FROM AUTHOR]

The aim of the article is to point out the need to introduce innovations, digitization and new advanced technologies in the so quickly developed enterprises. We want to define the assess the use of information and communication technologies in the Slovak industrial sector, as well as the implementation of ICT in production processes. This trend has the huge impact on the development of enterprises, countries and ultimately the entire world economy. In the final practise part of our paper, we implement our knowledges to Slovak industry and evaluate the level of their use. In this paper we have used a several scientific methods. Starting with collecting information, especially from scientific works from both, foreign and home authors, too. Subsequently, we have sorted them into individual chapters. From the scientific methods we used mainly paired methods as induction and deduction, analysis and synthesis. We used graphical and mathematical methods, which are mainly usedfor the clearer presentation of our results in the chart. [ABSTRACT FROM AUTHOR]

The aim of the paper is to investigate the relative importance of international vis‐à‐vis national technological linkages for international competitiveness for 19 industrial sectors. We estimate a dynamic model with an autoregressive structure in the dependent variable. In the paper competitiveness is captured both by cost competitiveness and by technological competitiveness. The main result is that while national linkages have a positive impact on the trade balance in several sectors (mostly scale intensive and specialised suppliers), this is not the case for international linkages. [ABSTRACT FROM AUTHOR]

The discussion regarding the balance between economical and performance for the pump design and manufacturing has been increasing in recent years. Of many intelligent innovations, the use of less costly materials for pump shaft is an interesting solution for the pump design. This solution can also be achieved by selecting less costly materials made from metal. Then, the less costly metal connected to electrical motor is joined with a more costly metal connected to the pump. Since both metals can be difference ones, an advance welding process to join both metals is then required. The friction welding process is expected to fulfill this requirement. In the friction welding, heat is generated during friction between these two dissimilar metals. The generated heat should achieve particular temperatures so that the two dissimilar metals can be joined. There are three types of friction welding, e.g. the stir friction welding, the linear friction welding and the continuous drive friction welding, which can be selected to join these two dissimilar metals. This paper is based on the authors' experience and literature review to discuss the application of friction welding for the pump design and manufacturing. [ABSTRACT FROM AUTHOR]

Introduction: As a result of Industry 5.0's technological advancements, collaborative robots (cobots) have emerged as pivotal enablers for refining manufacturing processes while re-focusing on humans. However, the successful integration of these cutting-edge tools hinges on a better understanding of human factors when interacting with such new technologies, eventually fostering workers' trust and acceptance and promoting low-fatigue work. This study thus delves into the intricate dynamics of human-cobot interactions by adopting a human-centric view. Methods: With this intent, we targeted senior workers, who often contend with diminishing work capabilities, and we explored the nexus between various human factors and task outcomes during a joint assembly operation with a cobot on an ergonomic workstation. Exploiting a dual-task manipulation to increase the task demand, we measured performance, subjective perceptions, eye-tracking indices and cardiac activity during the task. Firstly, we provided an overview of the senior workers' perceptions regarding their shared work with the cobot, by measuring technology acceptance, perceived wellbeing, work experience, and the estimated social impact of this technology in the industrial sector. Secondly, we asked whether the considered human factors varied significantly under dual-tasking, thus responding to a higher mental load while working alongside the cobot. Finally, we explored the predictive power of the collected measurements over the number of errors committed at the work task and the participants' perceived workload. Results: The present findings demonstrated how senior workers exhibited strong acceptance and positive experiences with our advanced workstation and the cobot, even under higher mental strain. Besides, their task performance suffered increased errors and duration during dual-tasking, while the eye behavior partially reflected the increased mental demand. Some interesting outcomes were also gained about the predictive power of some of the collected indices over the number of errors committed at the assembly task, even though the same did not apply to predicting perceived workload levels. Discussion: Overall, the paper discusses possible applications of these results in the 5.0 manufacturing sector, emphasizing the importance of adopting a holistic human-centered approach to understand the human-cobot complex better. [ABSTRACT FROM AUTHOR]

A new technology consisting of new and sustainable chemical polishing treatment for aluminum components with complex shapes, such as heat exchangers, manifolds, busbars, aerospace devices, etc., manufactured by Additive Manufacturing (AM) technologies is described in this paper. This technology will contribute to the development of a more efficient manufacturing process driven by AM, reinforcing the main idea of AM, which is based on reducing the amount of material and achieving cost savings through smart and improved designs. The present study shows a significant reduction in the surface roughness of consolidated AlSi10Mg metal parts manufactured by the SLM technique after carrying out the new chemical polishing post-process investigated in this work. Roughness values have been measured by mechanical and optical profilometry. The results obtained demonstrate the effectiveness of the chemical polishing, decreasing the roughness by up to 40%, being a reproducible and repeatable post-process. The presence of smut as solid residues on such types of chemical treatments has been also analyzed with XRF and ICP-MS techniques. The results obtained show that Si and Mg precipitates are removed from the metal surface at the last step of the investigated post-process. The percentages of the elements decrease from 25.0% to 8.09% Si and from 0.86% to 0.42% Mg, achieving the alloy smut-free composition on the metal surface. Tensile strength measurements have shown that the post-process described not only maintains the mechanical properties of the bulk material but, in comparison with non-post-processed parts, a slight improvement is observed with respect to the initial values, Young modulus (61.1 GPa to final 62.2 GPa), yield strength (from 236.8 to 246.7 MPa), and tensile strength (from 371.9 to 382.5 MPa) is observed, suggesting that the post-process has positive impact on the printed metal part. [ABSTRACT FROM AUTHOR]

Under the climate change background, green manufacturing is a critical path to realizing a low-carbon economy. The role of green products from manufacturing in economy-wide green transition has been discussed in the literature. In contrast, innovation in the industrial process, an important driver of climate change, has seldom been studied. This paper investigates the impact of green production process innovation on green manufacturing production using a fixed-effect SFA model. Furthermore, we discuss whether the impact of green production process innovation is conditioned on the economic development level, using a newly developed partial linear functional model. The results show that green production process innovation benefits green manufacturing, promoting sectoral carbon and energy efficiency. This paper further proposes policy implications, based on the findings that the green production process innovation's marginal effects vary with economic development level. [ABSTRACT FROM AUTHOR]

Industrial revolution 4.0 has enabled the advent of new technological advancements, including the introduction of information technology with physical devices. The implementation of information technology in industrial applications has helped streamline industrial processes and make them more cost-efficient. This combination of information technology and physical devices gave birth to smart devices, which opened up a new research area known as the Internet of Things (IoT). This has enabled researchers to help reduce downtime and maintenance costs by applying condition monitoring on electrical machines utilizing machine learning algorithms. Although the industry is trying to move from scheduled maintenance towards predictive maintenance, there is a significant lack of algorithms related to fault prediction of electrical machines. There is quite a lot of research going on in this area, but it is still underdeveloped and needs a lot more work. This paper presents a signal spectrum-based machine learning approach toward the fault prediction of electrical machines. The proposed method is a new approach to the predictive maintenance of electrical machines. This paper presents the details regarding the algorithm and then validates the accuracy against data collected from working electrical machines for both cases. A comparison is also presented at the end of multiple machine learning algorithms used for training based on this approach. [ABSTRACT FROM AUTHOR]

The aim of the paper is to present a hypothesis of upgrading within global value chains (GVCs). In Stage I, both backward and forward linkages are low at lower level of productivity growth, but it provides 'window of opportunity' to increase participation in GVC. Firms enter Stage II with increasingly backward linkages. Only those firms with enough accumulated technological capabilities for transforming into high value-added activities participates in GVC with increasingly forward linkages in Stage III. In Stage IV, both backward and forward linkages again decrease, albeit at a higher level of productivity growth, wherein the firms manage production processes fragmented at different locations. This hypothesis of 'upgrading within GVC in four stages' is verified while examining the pattern of backward and forward linkages of global electronics industry with a specific focus on the electronics industry of South Korea, Taiwan and Mexico. It was found that the electronics industry of South Korea and Taiwan exhibited the pattern of 'upgrading within GVC in four stages' while Mexican electronics industry got caught in the 'Stage II' or 'low value-added trap'. The proposition is examined from technological capability-building aspects of the systems of innovation approach. [ABSTRACT FROM AUTHOR]

Xylanases can boost pulp bleachability in Elemental Chlorine Free (ECF) processes, but their industrial implementation for producing bleached kraft pulps is not straightforward. It requires enzymes to be active and stable at the extreme conditions of alkalinity and high temperature typical of this industrial process; most commercial enzymes are unable to withstand these conditions. In this work, a novel highly thermo and alkaline-tolerant xylanase from Pseudothermotoga thermarum was overproduced in E. coli and tested as a bleaching booster of hardwood kraft pulps to save chlorine dioxide (ClO2) during ECF bleaching. The extremozyme-stage (EXZ) was carried out at 90 °C and pH 10.5 and optimised at lab scale on an industrial oxygen-delignified eucalyptus pulp, enabling us to save 15% ClO2 to reach the mill brightness, and with no detrimental effect on paper properties. Then, the EXZ-assisted bleaching sequence was validated at pilot scale under industrial conditions, achieving 25% ClO2 savings and reducing the generation of organochlorinated compounds (AOX) by 18%, while maintaining pulp quality and papermaking properties. Technology reproducibility was confirmed with another industrial kraft pulp from a mix of hardwoods. The new enzymatic technology constitutes a realistic step towards environmentally friendly production of kraft pulps through industrial integration of biotechnology. [ABSTRACT FROM AUTHOR]

Nowadays, manufacturing firms are dealing with the unpredictability of market requirements and the frequent changes induced by technological innovation. For this reason, firms are more and more addressing the need to be responsive at an affordable cost. To do so, they are required to develop a capability called reconfigurability. This paper is a review of the existing literature because the current need makes interesting to reflect on the state of the art of reconfigurability as a concept. This reflection has led to focus on reconfigurability characteristics for both their relevance and their relationships with managerial decisions in manufacturing. To this end, a framework has been proposed. It is based on system lifecycle and production levels. These two elements have been deduced from literature and identified as relevant dimensions for decision-making. [ABSTRACT FROM AUTHOR]

We are part of the digital transformation of society and industry. The digital transformation of industry is based on new technologies brought about by the fourth industrial revolution. The Internet of Things (IoT), Cloud Computing, Cyber–Physical Systems (CPS) and Big Data provide the digital link between machines and individuals in processes. This completely new system is based on efficient data collection, data analysis and immediate interventions in organizational processes based on the results of the analysis. Smart organizations are driven by data and not by models. By working efficiently with the vast amounts of data available, the smart organizations of the future can ensure business sustainability, increase competitiveness through process optimization and reduce costs. In general, the aim of this paper was to identify the means to achieve a paradigm shift from traditional organizations to smart organizations through the use of data in the context of integrating Industry 4.0 technologies. The aim of the research was to determine the extent to which different Industry 4.0 technologies are applied in the effective use of data from specific activities/processes in industrial organizations to bring about a paradigm shift from traditional organizations to smart organizations. The first part of the paper describes the theoretical background of the transition from traditional to smart organizations using selected Industry 4.0 technologies. The second part of the paper characterizes the research objective, the methods used in the paper and the basic statistics used to determine the research questions and hypotheses. The next section evaluates the research questions and hypotheses that were used to meet the research objective. The last part of the paper is a summary of the obtained results, based on which we conclude that the primary challenge for organizations in the Slovak Republic is to learn how to work with the collected data, the need for their appropriate structuring and subsequent archiving, which is manifested by the need for training and application of data analysts in a broader context. [ABSTRACT FROM AUTHOR]

Purpose: Quality 4.0 (Q4.0) leverages new emerging technologies to achieve operational excellence and enhance performance. Implementing Q4.0 in digital manufacturing can bring about reliable, flexible and decentralized manufacturing. Emerging technologies such as Non-Fungible Tokens (NFTs), Blockchain and Interplanetary File Storage (IPFS) can all be utilized to realize Q4.0 in digital manufacturing. NFTs, for instance, can provide traceability and property ownership management and protection. Blockchain provides secure and verifiable transactions in a manner that is trusted, immutable and tamper-proof. This research paper aims to explore the concept of Q4.0 within digital manufacturing systems and provide a novel solution based on Blockchain and NFTs for implementing Q4.0 in digital manufacturing. Design/methodology/approach: This study reviews the relevant literature and presents a detailed system architecture, along with a sequence diagram that demonstrates the interactions between the various participants. To implement a prototype of the authors' system, the authors next develop multiple Ethereum smart contracts and test the algorithms designed. Then, the efficacy of the proposed system is validated through an evaluation of its cost-effectiveness and security parameters. Finally, this research provides other potential applications and scenarios across diverse industries. Findings: The proposed solution's smart contracts governing the transactions among the participants were implemented successfully. Furthermore, the authors' analysis indicates that the authors' solution is cost-effective and resilient against commonly known security attacks. Research limitations/implications: This study represents a pioneering endeavor in the exploration of the potential applications of NFTs and blockchain in the attainment of a comprehensive quality framework (Q4.0) in digital manufacturing. Presently, the body of research on quality control or assurance in digital manufacturing is limited in scope, primarily focusing on the products and production processes themselves. However, this study examines the other vital elements, including management, leadership and intra- and inter-organizational relationships, which are essential for manufacturers to achieve superior performance and optimal manufacturing outcomes. Practical implications: To facilitate the achievement of Q4.0 and empower manufacturers to attain outstanding quality and gain significant competitive advantages, the authors propose the integration of Blockchain and NFTs into the digital manufacturing framework, with all related processes aligned with an organization's strategic and leadership objectives. Originality/value: This study represents a pioneering endeavor in the exploration of the potential applications of NFTs and blockchain in the attainment of a comprehensive quality framework (Quality 4.0) in digital manufacturing. Presently, the body of research on quality control or assurance in digital manufacturing is limited in scope, primarily focusing on the products and production processes themselves. However, this study examines the other vital elements, including management, leadership and intra- and inter-organizational relationships, which are essential for manufacturers to achieve superior performance and optimal manufacturing outcomes. [ABSTRACT FROM AUTHOR]