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This study aims to evaluate the impact of big data analytics (BDA) on the performance of healthcare supply chain management (HCSCMP) by examining both overall efficiency improvements and identifying critical success factors for effective implementation. Through a systematic literature review, the research investigates how BDA enhances real-time decision-making within healthcare supply chains (HCSCs) and identifies the key enablers required for successful BDA adoption. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs’ efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

This study aims to evaluate the impact of big data analytics (BDA) on the performance of healthcare supply chain management (HCSCMP) by examining both overall efficiency improvements and identifying critical success factors for effective implementation. Through a systematic literature review, the research investigates how BDA enhances real-time decision-making within healthcare supply chains (HCSCs) and identifies the key enablers required for successful BDA adoption. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs’ efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

Advanced design methods and manufacturing techniques are crucial for developing thermal management structures, essential for the efficient operation of complex equipment. This study provides a thorough review of design methodologies and advanced manufacturing technologies for thermal management materials and structures. It identifies key challenges and critically evaluates the integration of innovative design principles, such as biomimicry and topology optimization, into thermal management solutions. The analysis delves into the evolution of design theories and preparation techniques, with a specific focus on modern needs and research directions, particularly highlighting components fabricated using additive manufacturing and their effectiveness in meeting advanced thermal management requirements. Current research focuses on designing structures tailored to various cooling methods, including air‐cooling, liquid‐cooling, heat exchanger cooling, and heat pipe cooling. These designs utilize phase change materials, electrocaloric cooling, and thermoelectric cooling materials to achieve optimal thermal management performance. Additionally, emerging innovations like solid‐liquid mixed heat transfer and the elastocaloric effect are garnering increased interest. Enhancing the design of thermal management structures through rigorous numerical simulations is critical for improving engineering applicability. However, overcoming challenges related to the commercialization and practical utilization of these advanced structures remains a pressing need. [ABSTRACT FROM AUTHOR]

The use of big data analytics (BDAs) allows for the collection, management, and analysis of large volumes of data, which helps in making real-time decisions. This study aims to assess how the application of BDA impacts the performance of healthcare supply chain management (HCSCMP). Through a systematic literature review, the research explores how BDA enhances efficiency within healthcare supply chains (HCSCs) and identifies the critical factors enabling successful BDA implementation. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs' efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

With the integration and advancement of new generation information technology and manufacturing processes, big data in manufacturing presents solutions for transforming manufacturing model today. In order to mine the hidden knowledge value and potential capabilities of big data and facilitate the intelligent decision-making of business managers in complex dynamic manufacturing environments, a comprehensive study of intelligent manufacturing management driven by big data technologies was hereby carried out. Firstly, sources and characteristics of big data in the workshop were explored, providing an overview of the enabled big data technology including data collection, transmission, storage, computation, processing, visualization, and big data mining algorithms. Then, big data application scenarios were reviewed using the intelligent manufacturing workshop as the research context, and applications of big data in furniture workshops were discussed from four major aspects, job shop scheduling, quality control, prediction maintenance, energy management, and supply chain planning. Afterwards, data challenges for furniture intelligent manufacturing in the workshop were clarified, and a conceptual framework for furniture intelligent manufacturing was finally proposed based on big data technologies. Overall, the present research offers valuable insights and ideas for furniture workshops and future research directions. [ABSTRACT FROM AUTHOR]

Technological development is not a process determined only by the technology itself, the characteristics of which are largely decisive. Technology must be absorbed by an initially foreign system, in which a series of process-factors manifests itself, such as: strategy, top management, organization (company), technology and environment. The results are determined by each of these factors, but especially by the interactions, the connections between them. This paper develops a methodology for selecting and evaluating technologies for transfer based on groups of evaluation criteria (strategic, financial, industry / market technology consumers, internal, technological specifications, intangible effects) with the assignment of points (prioritization) starting from the performance descriptors for each criterion. The role of performance descriptors is not only to elucidate the relative value of technologies, but also to do so as objectively as possible.

The main purpose of this manuscript is to map the adoption of selected organisational concepts and advanced manufacturing technologies in manufacturing companies. A further objective of our research is to analyse the relationship between organisational concepts and advanced manufacturing technology in terms of their simultaneous use. Our research is based on a sample of 141 Slovenian manufacturing companies collected through the 2022-23 European Manufacturing Survey edition. For the purpose of this research, we have used simple statistics methods. The results indicate that manufacturing companies that introduced selected organisational concepts more frequently implement selected manufacturing technologies. [ABSTRACT FROM AUTHOR]

Flexibility and efficiency are twin capabilities of advanced manufacturing technologies (AMT). Much research has focused on AMT's role in bolstering manufacturing flexibility. Meanwhile, AMT's potential for efficiency is often disregarded, even proscribed by researchers, because that dampens the effect on flexibility. Yet, research shows that practitioners frequently implement AMT to pursue efficiency over flexibility. This problem has not been addressed in the literature. We approach this problem by viewing AMT through a strategic lens and examining AMT at the deployment level. Firms with different strategic goals must deploy AMT differently due to flexibility and efficiency often being opposite ends of a tradeoff. We identify two modes of deployment - AMTScale versus AMTScope - with characteristically different features, which explains AMT's ability to support opposed strategies. Our unique conceptualization puts into proper perspective the mixed empirical results reported in the literature. Drawing on the contingency theory, we find that firms deploying AMTScope (to support a 'differentiation' strategy) derive flexibility, while firms deploying AMTScale (to support a 'cost-leadership' strategy) sacrifice flexibility. [ABSTRACT FROM AUTHOR]

Industry 4.0 (I4.0) encompasses a plethora of digital technologies effecting on manufacturing enterprises. Most research on this topic examines the effects in the smart factory domain, focusing on production scheduling. However, there is still a lack of comprehensive research on the applications of I4.0 enabling technologies in manufacturing life-cycle processes. This paper is thus intended to provide a systematic literature review answering the following research question: What are the applications of I4.0 enabling technologies in the business processes of manufacturing companies? The study analyses 186 articles and the results show that production scheduling and control is the process most often investigated, while there is also an increasing trend in servitization and circular supply chain management. Moreover, there is extensive combined use of IoT, Big Data Analytics and Cloud, whose applications cover a wide range of processes. On the contrary, other technology like Blockchain is not as widely discussed in the domain of I4.0. This picture calls for a future research agenda extending the scope of investigation into I4.0 in manufacturing. Furthermore, the results of this research can prove extremely useful for practitioners who wish to implement one or more technologies, providing them with solutions for applications in manufacturing. [ABSTRACT FROM AUTHOR]

BACKGROUND: As the informational technology raising, 3D printing is applied widely in digital medicine. The importance of research and application of medical 3D printing focuses on the following perspectives: (1) printing organ pathology models and guid plate to aid in preoperative planning and adjuvant therapy; (2) creating custom prosthesis or implant scaffolds; and (3) creating personalized orthoses and braces; (4) fabricating viable tissues or organoids. OBJECTIVE: This paper described the application and advantages of 3D printing in digital medical industry, and summarized the current construction situations for 3D printing digital medical center in domestic and foreign market, as well as the registration approval of 3D printing medical devices, to provide experiences for the development of 3D printing digital medical industry. METHODS: Databases of Wanfang, CNKI and PubMed were searched for relevant articles published from January 2010 to February 2022 with the key words of “3D printing technology, 3D printed orthoses, 3D bioprinting, medical applications, medical center” in Chinese or English. A few classic early articles were included. By reading the titles and abstracts, repetitive studies, low-quality or irrelevant articles were excluded. Finally, 60 articles were included for review. RESULTS AND CONCLUSION: 3D printing technology and clinical medicine are tightly combined, and the cross-innovation of “medicine-industrial integration” has been realized through interdisciplinary innovative applications, and many scientific research innovations have been achieved. The construction of the 3D printing digital medical center will systematically train medical-engineering personnel for the hospital, and provide services such as image processing and cloud service system construction, and medical device printing, which also integrates digital medical technology and pushes the application of 3D printing to a new height in clinical practice. [ABSTRACT FROM AUTHOR]

One of the long-standing principles of phenomenological understanding is focused on the role of definition. Definitions are enablers in making something definite, distinct, or clear. This study aims to generate the definition of an emerging domain of Advanced Manufacturing Management using a literature review. First, an examination of Advanced Manufacturing Management (AMM) at an institutional level is provided, revealing institutions and courses that currently populate the domain. Second, a systematic literature review for AMM is conducted utilizing and triangulating between Web of Science, Science Direct/Elsevier, and Google Scholar. The results, supported by VOSviewer, suggest a dire need for a formal definition and conceptual foundations of AMM. Third, a proposed conceptual foundation that can enable a balanced development of AMM addressing the philosophical, theoretical, epistemological, ontological, axiological, axiomatic, methodology, methods, and applications aspects is suggested to support and holistically advance manufacturing and its problem domain. This conceptual foundation supports an alternative level of thinking, decision, action, and interpretation appropriate for the AMM problem domain, simultaneously advancing its science, engineering, applications, and practice. The article concludes with several challenges for the AMM field, a path forward for developing and advancing AMM as a field capable of providing a robust approach to dealing with emerging manufacturing-related issues. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) technology has the potential to significantly improve supply chain dynamics. The purpose of this paper is to investigate the impact of AM on spare parts supply chain. Three supply chain scenarios are investigated in this paper, namely conventional supply chain, centralised AM-based supply chain and distributed AM-based supply chain. Based on system dynamics simulations, this paper specifically compares three supply chain scenarios, in terms of total variable cost and carbon emission. The results show the spare part supply chain utilising AM is indeed superior to the traditional one in sustainable performance. It is also expected that AM can facilitate the spare parts supply chain to achieve more economic benefits along with its development. To our knowledge, this paper is one of the early studies that explores the impact of AM on supply chain performance and quantitatively examines the superiority of utilising AM in spare parts supply chain. Some suggestions are also provided to help managers adopting AM in their spare parts supply chains. [ABSTRACT FROM AUTHOR]

Based on the phenomenal changes that additive manufacturing (AM) has brought to industries and markets, managerial approaches should be re-examined and developed to take advantage of emerging opportunities. This revolutionary technology is dramatically changing business and innovation models, shrinking supply chains and altering the global economy. For example, 3D printing shifts production locations closer to customers and leads to free-form product design as well as sustainable manufacturing. Several studies have been conducted on AM technology, but the research stream on AM management is still developing, with studies dispersed in journals across different research areas. Our study presents both systematic and quantitative analyses of the literature, including co-citation analysis, factor analysis and multidimensional scaling, to explore the structure of the AM research domains in the scope of management, business and economics. We found eight main research streams: AM technology selection, supply chain, product design and production cost models, environmental aspects, strategic challenges, manufacturing systems, open-source innovation and business models and economics. Finally, based on the results of our in-depth analysis of the literature, we found nine promising future research directions. [ABSTRACT FROM AUTHOR]

This paper deals with the development of an online methodology for the automatic control and alignment of spur gears. The proposed methodology works on a set of points acquired on the workpiece surfaces by means of a manufacturing machine equipped with a set of sensors for dimensional measurements. A mathematical algorithm is developed to correct the position of the gear; it constitutes the main part of the developed monitoring and control system: it is able to real-time analyse the collected data of each measure and provide the orientation parameters that minimise the residual positioning errors. The methodology is first tested on simulated data-sets and the final workpiece configuration exhibits a good reproducibility. The tests executed on real data, acquired both through a coordinate measuring machine and the sensor system integrated into the manufacturing machine, confirm this result. The employment of this automation system allows to shorten the time necessary for the alignment process and improves the precision of the final positioning, leading to enhanced quality of the products and higher process flexibility, compared to the currently employed manual operation. [ABSTRACT FROM PUBLISHER]

Collaborative robots (cobots) are emerging in manufacturing as a response to the current mass customization production paradigm and the fifth industrial revolution. Before adopting this technology in production processes and benefiting from its advantages, manufacturers need to analyze the investment. Therefore, this study aims to develop a decision-making framework for cobot adoption, incorporating a comprehensive set of quantitative and qualitative criteria, to be used by decision-makers in manufacturing companies. To achieve that objective, a qualitative study was conducted by collecting data through interviews with key actors in the cobot (or advanced manufacturing technologies) adoption decision process in manufacturing companies. The main findings of this study include, firstly, an extensive list of decision criteria, as well as some indicators to be used by decision-makers, some of which are new to the literature. Secondly, a decision-making framework for cobot adoption is proposed, as well as a set of guidelines to use it. The framework is based on a weighted scoring method and can be customizable by the manufacturing company depending on its specific context, needs, and resources. The main contribution of this study consists in assisting decision-makers of manufacturing companies in performing more complete and sustained decision analyses regarding cobots adoption. • Financial aspects, safety, productivity, and ergonomics are important criteria. • A decision-making framework for cobot adoption based on the weighted scoring method • Incorporating quantitative and qualitative criteria in the adoption decision • The framework is customizable to the company's context, needs, and resources. • Empirical perspective of decision-makers in manufacturing companies was considered. [ABSTRACT FROM AUTHOR]

Bamboo material has excellent properties and is suitable for making bamboo furniture. Bamboo furniture is a traditional form of furniture made from bamboo with a low degree of industrialisation. The diverse development methods and profound cultural meanings behind bamboo furniture should be further explored to strengthen inheritance and innovation. This paper first summarises the characteristics and development status of bamboo furniture via a brief literature review. Then, through case studies and questionnaire surveys, the aesthetic trends of modern bamboo furniture design were analysed, and various ideas for innovation were proposed. The mode and path of the future development of bamboo weaving were discussed from the perspective of accelerating modernisation. To achieve sustainable development of bamboo furniture, to promote bamboo culture, and to enable bamboo enterprises to establish a good brand image, it is necessary to use the interactive design platform to coordinate the relationship between users, enterprises, and producers, and to grasp the balance between traditional craftsmanship and modern design and manufacture through modern advanced manufacturing technology and parametric design. [ABSTRACT FROM AUTHOR]

Based on Upper Echelon Theory (UET), this study established and examined the impact of upper managers ‘s characteristic (CEO) on choosing a cost leader strategy (CL), using cost management system (CMS) information in the process CEO ‘s strategic decisions. As well as considering the moderator role of advanced manufacturing technology (AMT) in some relationships. This study used SmartPLS3 software to evaluate measurement model and structure model. The results indicated that: (1) the positive effects of all direct relationships are accepted and; (2) the moderator role of AMT in the relationships between education background—choice of CL; Education background—CMS are both positive and statistically significant. This results reinforced for the important role of using CMS information, CEO ‘s demographic characteristic (eduction background), AMT ‘s moderator role. Then, this result will help managers to design a CMS effectively suitable to CEO and strategy of firm, enhancing financial performance of manufacturer.

Investment appraisal in advanced manufacturing technologies (AMTs) has been receiving considerable attention over the past three decades. As stated in numerous studies, traditional engineering economic methods cannot adequately justify investments in AMTs. Thus, beside these methods, some other solutions have been proposed in this field. The methods applied in the evaluation of AMTs can be classified into four groups including economic, strategic, analytical and integrated methods. In this paper, an integrated model is presented for the evaluation of AMTs. The model is developed according to a fuzzy multi-criteria decision making procedure. It is assumed that a group of decision makers evaluate different AMT alternatives according to certain strategic and economic criteria. The importance of the criteria and the weights of the alternatives versus the criteria are expressed using linguistic variables set by the decision makers. To compute the economic criterion of each alternative, a linear program with chance constraints is proposed. Finally, using different fuzzy operators, the AMT alternatives are scored and ranked. In this regard, an example is presented to show the performance of the model. [ABSTRACT FROM AUTHOR]

Industrial robots, which enable manufacturing firms to produce high-quality products in a cost-effective manner, are important components of advanced manufacturing technologies. The performance of industrial robots is determined by multiple and conflicting criteria that have to be simultaneously considered in a robust selection study. In this study, a decision model based on fuzzy linear regression is presented for industrial robot selection. Fuzzy linear regression provides an alternative approach to statistical regression for modelling situations where the relationships are vague or the data set cannot satisfy the assumptions of statistical regression. The results obtained by employing fuzzy linear regression are compared with those of earlier studies applying different analytical methods to a previously reported robot selection problem. [ABSTRACT FROM PUBLISHER]

The surface inspection of flat-panel glass is important in manufacturing processes. In this study, an experimental analysis based on dark-field laser scattering was performed to inspect micro-defects in flat-panel glass for infrared cut-off filters. The laser scattering parameters were investigated and scattering light paths analysed. On the basis of these results, a structured mechanism was designed and an experimental inspection system developed using the mechanism. By examining the effect of changing parameter values, it was found that two dark-field laser scattering parameters—the incident angle of the laser and the viewing angle of the camera—are critical for the intensity and distribution of the scattering light for accurate and robust surface inspection. Also, the difference of these angles is very important. Based on the design of experiment, previous experimental results are evaluated and predominant parameters are optimally determined. The results of the experimental inspection system demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Selection of advanced manufacturing technologies (AMTs) is an important yet complex decision which requires careful consideration of various performance criteria. This paper proposes the use of data envelopment analysis (DEA) with double frontiers for the selection of AMTs, which considers not only the best (optimistic), but also the worst (pessimistic) relative efficiencies of each AMT. Compared with the traditional DEA, the DEA approach with double frontiers can identify the best AMT correctly and easily without the need to impose any weight restriction or the need to calculate the cross-efficiency matrix, which requires a large number of computations and may also result in inconsistent conclusions by aggressive and benevolent cross-efficiency models. Four numerical examples are examined using the DEA approach with double frontiers to illustrate its simplicity and usefulness in AMT selection and justification. [ABSTRACT FROM AUTHOR]

The traditional kanban system with a fixed number of cards does not work satisfactorily in an unstable environment. With the adaptive kanban-type pull control mechanism, the number of kanbans is allowed to change with respect to the inventory and backorder level. It is required to set the threshold values at which cards are added or deleted, which is part of the design. Previous studies used local search and meta-heuristic methods to design an adaptive kanban system for a single stage. In a multi-stage system the cards are circulated within the stage and their presence at designated positions signals to the neighbouring stages details concerning the inventory. In this work, a model of a multi-stage system adapted from a traditional and adaptive kanban system is developed. A genetic and simulated annealing algorithm based search is employed to set the parameters of the system. The results are compared with a traditional kanban system and signs of improvement are found. The numerical results also indicate that the use of a simulated annealing algorithm produces a better solution. [ABSTRACT FROM AUTHOR]

This paper explores how transaction attributes of technology affect differences in the relationship between technology buyers and suppliers. It also examines the impact on performance of different patterns of relationship between technology buyers and suppliers. Data obtained from 147 manufacturing firms in Malaysia are used to test several hypotheses, which were derived from a review of the literature on technology, transaction cost theory and buyer-supplier relationships (BSR). The research results indicate that the higher the level of technological complexity, specificity and uncertainty, the more firms are likely to engage in a closer relationship with technology suppliers. Even though the majority of firms reported improvements in their performance, results indicate that firms demonstrating a closer relationship with technology suppliers are more likely to achieve higher levels of performance than those that do not. It is also shown that with high levels of transaction attribute, implementation performance suffers more when firms have weak relationships with technology suppliers than with moderate and low levels of transaction attribute. [ABSTRACT FROM AUTHOR]