Mass Customization Research Articles

The Development of Manufacturing Industry Revolutions from 1.0 to 5.0

Industry 5.0 is a term used to describe how the manufacturing industry is being modernized and how human and machine collaboration is being fostered to increase efficiency and speed up results. By integrating digital technologies, this revolutionary transformation not only creates tailored goods that increase customer happiness but also establishes a new paradigm in supply chain management and manufacturing. Complex problems are addressed by using artificial intelligence and machine learning to the analysis of large amounts of manufacturing data. Gaining a competitive edge and promoting economic growth requires embracing IoT and the Industry 5.0 phenomenon in today's fast-paced corporate environment, which is defined by technical breakthroughs and globalization. Because they work in unison with human intelligence, robotics' contribution to this revolution enhances the accuracy of computation and prediction in industrial automation systems. In the age of technology, rapid changes are driving the development of mass customization and smart manufacturing, with robots playing a crucial role in enhancing human talents. This essay examines the historical background of industrial revolutions and the effects of Industry 4.0 and Industry 5.0 on society and manufacturing. It also highlights the salient characteristics and potential applications of these next industrial revolutions, culminating in a summary of the differences between Industry 4.0 and Industry 5.0.

Exploring the Feasibility of Advanced Manufacturing for Mass Customization of Insoles in the Context of ESG

Exploring the Feasibility of Advanced Manufacturing for Mass Customization of Insoles in the Context of ESG

Strategies for Software and Hardware Compatibility Testing in Industrial Controllers

Mass customization, small batch sizes, high variability of product types and a changing product portfolio during the life cycle of an industrial plant are current trends in the industry. Due to an increasing decoupling of the development of software and hardware components in an industrial context, compatibility problems within industrial control systems arise more and more frequently. In this publication, a strategy concept for compatibility testing is derived and discussed by means of a literature review and applied research. This four-phase strategy concept identifies incompatibilities between software and hardware components in the industrial control environment and enables test engineers to detect problems at an early stage. By automating the compatibility test on an external I-PC, the test can be run both when new software is installed on the industrial controller and when the controller is restarted. Thus, changes to the components are constantly detected and incompatibilities are avoided. Furthermore, early incompatibility detection can ensure that a system remains permanently operational. Based on a discussion, additional strategies are identified to consolidate the robustness and applicability of the presented concept.

Optimization of Personalized Mass Customization Building Portfolio by Integrating BIM and NSGA Algorithms

The objective of this study is to optimize the personalized mass customization building portfolio by using BIM and NSGA algorithms to achieve the desired balance between cost and efficiency. The study uses BIM software for cost simulation, and NSGA-II algorithm for multi-objective optimization. The mathematical model of building cost and duration is constructed and the multi-objective optimization algorithm is applied to achieve optimization under multiple objectives. The results of the study show that after 20,000 generations of iterations, 191 Pareto solutions are determined to be valid, and the stability and uniform distribution of the optimization objectives are verified, with the percentage of valid solutions reaching 92\%. In the conducted VIKOR scenario analysis, three different cost-effective optimization schemes are proposed depending on user preferences. The method of integrating BIM and NSGA algorithm can effectively improve the cost-effectiveness of building design, and provides a feasible and efficient optimization path for personalized mass-customized buildings.

Enhancing sustainability in mass customisation of consumer electronics with salvage value through supply chain financing

ABSTRACT The consumer electronics industry is crucial in the global shift toward sustainability. To meet customers’ personalised needs efficiently and reduce production costs, electronic product suppliers increasingly focus on Mass Customization (MC) and modular production. Implementing a buyback policy for unsold module products with salvage value is a sustainable practice that reduces waste. This study explores two buyback support financing tools to enhance sustainability in the industry, enabling successful MC production. We also investigate how the salvage value based on modularity level and the buyback policy impact operational and financing decisions in the Mass Customization Supply Chain (MCSC). The research reveals that a higher modularity level positively impacts supplier’s profits and optimal capacity levels under both financing strategies. Consequently, this study offers valuable insights into elevating sustainability practices and optimising operational and financing decisions in the context of MC within the consumer electronics industry.

A parametric design framework for the mass customization of bicycle helmet

Cluster analysis of 3D head shapes plays a crucial role in the mass customization design of products related to the head. Head shapes exhibit variations across different races, and designing helmets exclusively for Chinese individuals cannot solely rely on or reference foreign head models. Currently, research on cluster analysis of Chinese head shapes is limited, especially concerning shape variances. To address this, we developed an improved k-medoids algorithm and integrated Cluster Validity Index as an assessment metric. This enabled us to cluster 339 Chinese young males aged 18 to 30 into 7 groups based on their head shapes. By comparing our improved algorithm to the traditional k-medoids method, we affirmed its superiority in achieving higher sample participation rates and reducing inter-cluster sample disparities. To simplify the helmet design and editing process, and to improve the efficiency of mass customization, we have developed a parametric modeling program for bicycle helmets based on the head shape clustering results. Results from the Helmet Fit Index and stress simulation analysis demonstrate that our approach significantly enhances helmet fit and wearer comfort.

The relationship between mass customization and sustainable performance: The role of firm size and global E-commerce

The formation of mass customization competencies is crucial for the increasing number of manufacturing companies in modern times. This study assessed the relationship between mass customization capability and its determinants on sustainable performance. Additionally, it explores the mediating role of mass customization capability and sustainable performance, while also examining the moderating effects of firm size and cross-border eCommerce in these associations. The study used online survey data from 339 manufacturing small-to-medium-sized enterprises in China to test the hypothesized relationships. The collected data were analyzed using partial least square structural equation modeling and necessary condition analysis. The results indicated that flexible manufacturing competencies, modular product architecture, and customer relationship management are significantly and positively connected to mass customization capability. Moreover, the study observed that mass customization capability and competitive pressure have a significant positive influence on the sustainable performance of Chinese manufacturing SMEs. The findings also revealed that firm size and cross-border e-commerce engagement have a negative and positive moderating effect, respectively, between mass customization capability on sustainable performance, which confirms a relatively higher effect of customization capability on sustainable performance among smaller firms and firms engaged in cross-border eCommerce. Fundamentally, these findings can lead to the development of a comprehensive framework to promote mass customization capability, cross-border e-commerce, and sustainable development of manufacturing small-to-medium-sized enterprises China.

Robotic fabrication of clay acoustic resonators

Digital fabrication offers the potential for the creation of complex geometries and mass-customized products; however, most 3D printers do not scale sufficiently to create architectural scale components. Robotic fabrication methods may bridge the gap, offering the possibility of architectural-scale 3d-printing capabilities. It has been found that the combination of multiple Helmholtz resonators tuned to different frequencies can create broadband absorption. This research pairs CAD parametric design with robotic clay extrusion as a method of acoustic resonator mass customization. The history of architectural acoustics together with recent archeological discoveries unveils a long-established practice of using clay vases as acoustic devices. And while the efficacy of these vases in historical settings has been contested, the use of large arrays of carefully tuned acoustic vases remains largely unexplored in contemporary practice. This paper presents the acoustic vases' unique history, defines its geometry and performance, and projects the potentials of the acoustic vase in current practice through modelling, simulation, and fabrication. A full-scale prototype wall with 126 robotically 3d-printed clay resonator vases was designed and constructed. The 1:1 prototype was shown in the “Robotic Clay,” which was exhibited at the Canadian Clay and Glass Gallery in Waterloo, Canada.

РОЗВИТОК ІНДУСТРІЇ 4.0 ТА ЇЇ ВПЛИВ НА ЕКОНОМІЧНУ БЕЗПЕКУ КРАЇН

The digital paradigm of the global economy is being built based on the study of current Industry 4.0 trends. The formation of the digital economy in the relevant areas means the recognition of a certain dependence of the future development of the country and its economic security on the degree of its mastering of innovations and digital technologies.The purpose of the study is to analyze trends in the development of Industry 4.0 on an international scale and establish its impact on the economic security of countries. To solve the set goal, a theoretical research concept of concepts related to Industry 4.0 was formed during the research; the stimulators and destimulators of the transition of the studied countries to the concept of Industry 4.0 are singled out; a SWOT analysis of the implementation and development of Industry 4.0 was carried out and the world trends of the implementation and development of Industry 4.0 were determined. The authors researched scientific publications highlighting concepts related to the definition of Industry 4.0, such as: mass customization, servitization, Logistics 4.0, new systems in the development of products and services, knowledge management, smart product, adaptation to human needs, circular economy, lean production , Recycling 4.0, systems science, flexible manufacturing, smart factory and digital transformation. The experience of the implementation of Industry 4.0 measures in the EU member states is positive, the analysis of which confirms the following stimulators, the emphasis on which is quite appropriate when implementing initiatives in Ukraine: the involvement of industry, cooperation between various participants, the involvement of regional authorities and state funding. The authors carried out a SWOT analysis, which made it possible to determine the strengths and weaknesses, opportunities and threats of economic development in the context of the implementation of Industry 4.0. An analysis of the dynamics of the spread of the Internet among the population in comparison with the size of the population was carried out. An analysis of the number of investments in the development of new Industry 4.0 technologies was carried out. The key features and advantages of economic development in the conditions of Industry 4.0 are revealed. Automation, digital technology and their implementation in all spheres of the enterprise are highlighted Therefore, the activation of the use of the opportunities of Industry 4.0 by the countries of the world to apply the achievements of scientific and technological progress and obtain additional benefits from the implementation of strategies for the digital development of the country's economy. Industry 4.0 requires companies and countries to actively develop flexibility, innovation and innovative thinking in order to always be competitive in the market.

SPECIFICS OF IMPLEMENTING SMART MANUFACTURING IN INDUSTRIAL SMALL AND MEDIUM-SIZED ENTERPRISES: BENEFITS AND LIMITATIONS

Purpose. The aim of the article is to determine the mechanisms for solving the technological and technical limitations of data management during the automation of the production process at industrial enterprises, as well as the economic advantages and limitations created by the introduction of smart production at small and medium-sized industrial enterprises. Methodology of research. The theoretical and methodological basis of the research is the scientific works of leading scientists and practicing entrepreneurs regarding the features and technology of implementing smart production at industrial enterprises. The following general scientific methods were used in the research process: comparison – to study the approaches of the largest producing countries to the management and stimulation of the development of smart production; analysis and synthesis – to analyse the state of implementation of smart production at small and medium-sized industrial enterprises; abstract and logical – for expressing own assumptions and formulating conclusions, graphic – for visual illustration of the conceptual model of optimization of software and hardware of SMEs for data processing of enterprises. Findings. It has been established that the leading technologies forming the system of smart production - the industrial Internet of Things, neural networks based on artificial intelligence and blockchain technology – solve the following technological limitations that existed under the centralized server infrastructure: infrastructure overload due to the increase in the consumption of computing resources (solved as a result of optimization the speed of transaction accounting due to the introduction of artificial neural networks based on artificial intelligence); problems of stakeholder authentication and platform compatibility (solved as a result of automating registration of participants, transactions and as a result of automating the execution of transactions due to smart contracts within the framework of open blockchain technology); insufficient integrity and confidentiality of the data register as a result of compatibility and authentication problems (solved due to the technology of distributed accounting of transactions (blockchain), which allows to avoid falsification of data). It was found that the main economic advantage as a result of the implementation of the mentioned technologies within the framework of the smart production system is the possibility of mass customization of production at the level or almost at the level of the costs of standard mass production. It is specified that these technologies are appropriate for implementation by high-tech industrial enterprises producing products with high added value. Originality. The theoretical aspects of establishing direct and indirect economic benefits from the implementation of a smart production system at industrial small and medium-sized enterprises, approaches to optimizing production in the direction of product customization have gained further development. Practical value. Formulated approaches and recommendations for solving problems related to data processing during the automation of the production process - as a set of technological limitations, as well as an approach for solving technological limitations for the manufacture of customized products can be used at innovation-oriented industrial enterprises, in particular, medium and small ones. Key words: smart production, small and medium enterprises, industrial Internet of things, artificial intelligence, blockchain technology, automation, production, data processing.

Proposal of Industry 5.0-Enabled Sustainability of Product–Service Systems and Its Quantitative Multi-Criteria Decision-Making Method

In the wake of Industry 4.0, the ubiquitous internet of things provides big data to potentially quantify the environmental footprint of green products. Further, as the concept of Industry 5.0 emphasizes, the increasing mass customization production makes the product configurations full of individuation and diversification. Driven by these fundamental changes, the design for sustainability of a high-mix low-volume product–service system faces the increasingly deep coupling of technology-driven product solutions and value-driven human-centric goals. The multi-criteria decision making of sustainability issues is prone to fall into the complex, contradictory, fragmented, and opaque flood of information. To this end, this work presents a data-driven quantitative method for the sustainability assessment of product–service systems by integrating analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods to measure the sustainability of customized products and promote the Industry 5.0-enabled sustainable product–service system practice. This method translates the sustainability assessment into a multi-criteria decision-making problem, to find the solution that meets the most important criteria while minimizing trade-offs between conflicting criteria, such as individual preferences or needs and the life cycle sustainability of bespoke products. In the future, the presented method can extend to cover more concerns of Industry 5.0, such as digital-twin-driven recyclability and disassembly of customized products, and the overall sustainability and resilience of the supply chain.

Business model innovation of 3D-printing garment enterprises in digital transformation: business model innovation canvas approach

Purpose3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.Design/methodology/approachA business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.FindingsFirst, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.Research limitations/implicationsThe new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.Practical implicationsThe new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.Originality/valueA new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

Order sequencing for a bucket brigade seru in a mass customization environment

In a mass customization environment, customer demands may change dramatically, which challenges conventional production systems. Seru production system (SPS) is a key to deal with changing varieties and fluctuated volumes. A bucket brigade seru is a divisional seru, in which partially cross-trained workers are organized as a bucket brigade. This paper studies an order sequencing problem for a bucket brigade seru with the objective of minimizing makespan. Dynamic behavior of a bucket brigade seru is modeled. Properties of the problem are presented that alternating the processing sequence of some products does not affect makespan. These properties provide factory managers with flexibility to adjust products processing sequence in case of changes in customer demands or lacks in materials. Six local search algorithms are developed using these properties, which combine three policies of selecting products in the operations of swap and insert. A bucket brigade local-search-based differential evolution (BLaDE) algorithm is proposed for the addressed problem, which may incorporate one of the six local search algorithms according to various scenarios. More than 14,000 instances are generated to evaluate the algorithms in terms of effectiveness, convergence, and stability. Experimental results demonstrate the superiority of BLaDE in volatile markets.

Industry 4.0 Implementation Drivers in Manufacturing Companies in Algeria: A Structural Analysis via ISM Method

The new industrial era is characterised by an incredible speed of development, in addition to fierce competition, which prompts companies to quickly adopt Industry 4.0 to maintain their position in the future industrial market. This paper aims to identify the main drivers that facilitate the implementation of Industry 4.0 in manufacturing companies in Algeria. The Interpretative Structural Modelling (ISM) method and the Cross-Impact Matrix Multiplication Applied to a Ranking (MICMAC) method were used. The ISM-MICMAC method aims to determine interrelationships and levels of influence between different factors. This allows the identification of the key drivers for the success of Industry 4.0 implementation in manufacturing companies. The results showed that awareness of the concept of Industry 4.0, research and development, support and vision of senior management, and society acceptance of the technology, in addition to cooperation and openness, are the most important drivers that contribute to the success of the implementation of Industry 4.0. Moreover, improving production, maintenance efficiency, and improving mass customisation also play a crucial role in the adoption of Industry 4.0 in manufacturing companies.

Improvement of Industrial Maintenance Plans through Assistance-Driven Reliability-Centered Maintenance and Case-Based Reasoning Design

The present work builds on studies where the industrial market is currently characterized by a highly variable demand in terms of the quantities and flexibility of manufacturing or mass customization, which translates into a more demanding production context in terms of the continuous changes that are required in the production systems, the effect of which results in an increase in the fatigue of the machines that make up the production systems. However, current production systems tend to use highly communicative and sensorized cyber–physical systems; these characteristics can be used to integrate them into decision-assisted systems to improve the availability of the industrial plant. The developed assisted system focuses on collecting and taking advantage of historical knowledge of industrial plant failures and breakdowns. By ideally integrating the reliability-centered maintenance (RCM) methodology and case-based reasoning (CBR) algorithms implemented in a Java application, it is possible to design maintenance plans that are adjusted to the real and changing operational context of any industrial plant. As a result, faster and more accurate decisions are made, because they are based on data. This article focuses on improving certain aspects of the developed assisted system by adding more value by incorporating fuzzy logic (FL) techniques. The aim is to improve the way of entering information about risk factors and their relative importance by incorporating natural language instead of a numerical score, resulting in increased precision in the calculation of the risk priority number (RPN) of the new cases that are incorporated into the assisted system. On the other hand, an attempt has been made to correct two of the main inherent and recognized weaknesses in the classic RPN calculation method by implementing an appropriate mix of fuzzy logic techniques.

Apparel Mass Customization and its Applicability

Apparel Mass Customization and its Applicability

Product family modeling technology for customized cosmetic packaging design based on basic-element theory

BackgroundAs the market demands change, SMEs (small and medium-sized enterprises) have long faced many design issues, including high costs, lengthy cycles, and insufficient innovation. These issues are especially noticeable in the domain of cosmetic packaging design. ObjectiveTo explore innovative product family modeling methods and configuration design processes to improve the efficiency of enterprise cosmetic packaging design and develop the design for mass customization. MethodsTo accomplish this objective, the basic-element theory has been introduced and applied to the design and development system of the product family. ResultsBy examining the mapping relationships between the demand domain, functional domain, technology domain, and structure domain, four interrelated models have been developed, including the demand model, functional model, technology model, and structure model. Together, these models form the mechanism and methodology of product family modeling, specifically for cosmetic packaging design. Through an analysis of a case study on men’s cosmetic packaging design, the feasibility of the proposed product family modeling technology has been demonstrated in terms of customized cosmetic packaging design, and the design efficiency has been enhanced. ConclusionThe product family modeling technology employs a formalized element as a module configuration design language, permeating throughout the entire development cycle of cosmetic packaging design, thus facilitating a structured and modularized configuration design process for the product family system. The application of the basic-element principle in product family modeling technology contributes to the enrichment of the research field surrounding cosmetic packaging product family configuration design, while also providing valuable methods and references for enterprises aiming to elevate the efficiency of cosmetic packaging design for the mass customization product model.

Influences The Sustainability Of Business Continuity Through Mass Customization On Embroidery Smes In West Bandung Regency

At this time, MSMEs are an important part of the economy in Indonesia, one of them is in the West Java region. It was recorded that in 2021 the number of MSMEs in West Java was 6,257,390 and West Bandung Regency was the area that experienced a significant increase. The categories of the business are accessories, batik, embroidery, craft, fashion, services/others, convection, culinary, food and drink. However, the covid-19 pandemic has caused business actors, especially the embroidery sector that must be work harder in order to survive in the pandemic era. The lack of entrepreneurial innovativeness in business success is can influence a decrease in sales and the success of a business can be seen from business actors who making mass adjustments in terms of production (mass customization). Therefore, business actors are required to be able to maintain their business. On this research using a descriptive and associative methods. Descriptive research explains that characteristic or gap can be used as a basic to solving business problem. On this research, descriptive research explains characteristic and variable function like entrepreneurial innovativeness, mass customization, and business contuinity. The location of this research is in West Bandung Regency, and the research subject were 70 embroidery business actors in West Bandung Regency. Data collection techniques is using library research, then continued with distributing questionnaires and interview. Data analysis techniques is using path diagrams assisted by SEM-PLS software. The result on this research show that entrepreneurial innovativeness mediated by mass customization has an effect on business continuity.

Human-robot collaborative task planning for assembly system productivity enhancement

PurposeIn the current era of Industry 4.0, the manufacturing industries are striving toward mass production with mass customization by considering human–robot collaboration. This study aims to propose the reconfiguration of assembly systems by incorporating multiple humans with robots using a human–robot task allocation (HRTA) to enhance productivity.Design/methodology/approachA human–robot task scheduling approach has been developed by considering task suitability, resource availability and resource selection through multicriteria optimization using the Linear Regression with Optimal Point and Minimum Distance Calculation algorithm. Using line-balancing techniques, the approach estimates the optimum number of resources required for assembly tasks operating by minimum idle time.FindingsThe task allocation schedule for a case study involving a punching press was solved using human–robot collaboration, and the approach incorporated the optimum number of appropriate resources to handle different types of proportion of resources.Originality/valueThis proposed work integrates the task allocation by human–robot collaboration and decrease the idle time of resource by integrating optimum number of resources.

Binder jetting 3D printing in fabricating pharmaceutical solid products for precision medicine.

Current treatment strategies are moving towards patient-centricity, which emphasizes the need for new solutions allowing for medication tailored to a patient. This can be realized by precision medicine where patient diversity is considered during treatment. However, the broader use of precision medicine is restricted by the current technological solutions and rigid manufacturing of pharmaceutical products by mass production principles. Additive manufacturing of pharmaceutical products can provide a feasible solution to this challenge. In this review, a particular subtype of additive manufacturing, that is, binder jetting 3D printing, is introduced as a solution for fabricating pharmaceutical solid products that can be considered as precision medicine. Technical aspects, practical applications, unique advantages and challenges related to this technique are discussed, indicating that binder jetting 3D printing possesses the potential for fabricating already new product prototypes, where diversity in patient treatment in terms of the needs for specific drug type, dose and drug release can be accounted. To further advance this type of mass customization of pharmaceuticals, multidisciplinary research initiatives are needed not only to cover the engineering aspects but also to bridge these innovations with patient-centric perspectives.