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Small- and medium-sized manufacturing enterprises (SMMEs) face intense competitiveness, necessitating ever greater productivity. Enterprises struggle to meet the demand for customized products while maintaining their productivity. The transition from mass customization (MC) to mass personalization (MPe) leads to a further increase in product variety and, thus, complexity. Digital transformation alone is not sufficient to achieve MPe and traditional adoption of modularity no longer ensures enterprise competitiveness in this context of increased variety. The synergy between modularity concepts could enhance the efficiency of this design strategy. This study is part of a research plan to develop an effective modularity implementation strategy addressing MPe. The aim of this article is to identify the main concepts and tools to be considered in an implementation strategy. Concepts and tools are grouped into four combinations according to the level of product variety in different production strategies. This preliminary work serves as the foundational research for a larger research plan aimed at adapting and validating a modular product development strategy that incorporates these modularity concepts. [ABSTRACT FROM AUTHOR]

In the Internet era, the industrial Internet platform has become a bridge between customers and enterprises. In addition, with the continuous improvement of customers' living standards, customers not only meet the basic needs for the functionality of products, but also yearn to participate in the production process of products and interactive experience activities with enterprises while pursuing high quality. In view of the difficulties in identifying and capturing the dynamically changing needs of customer- product interaction whole life cycle under the new environment of industrial Internet, and the problem of large amount and redundancy of demand data, this paper develops a set of models and methods covering the identification, definition, acquisition and parsing of customer needs, which provides theoretical support and decision-making basis for enterprises to accurately capture and predict customer needs, excavates potential market customers of enterprises, and realizes value-added of the value chain. Moreover, the methodology of personalized requirements for CILC proposed in this paper is helpful to the transformation of enterprise manufacturing model from mass manufacturing to mass customization and even to mass personalization. It can reduce enterprise production costs, and improve customer satisfaction and service experience. [ABSTRACT FROM AUTHOR]

After mass production and then mass customization, the time is almost ripe for mass personalization. The goal is to offer unique products designed for the needs of each customer. However, production in larger series of products also has its advantages, and the promise of "lot size one" is still far from being the norm in several sectors of the economy. As a result of an action research project in a small household ceramic producer, this paper explores the potential of a hybrid strategy. Augmented digital engineering is adopted to (1) ensure customer participation along the entire product design lifecycle, (2) maintain the benefits of modularization and low cost, (3) minimize the waste of time and materials during product design, and (4) seek a minimum trade‐off between customer desires and engineering strategy. For theory, our work describes Industry 4.0 technology's role in achieving individual customer interaction and value co‐creation in hybrid strategies of mass customization and mass personalization. For practice, we present an example of technological architecture to implement augmented digital engineering in Industry 4.0, accessible to scenarios of hand‐intensive work and creative design processes. [ABSTRACT FROM AUTHOR]

In order to meet the changing needs of customers, the manufacturing model of products is constantly changing from mass manufacturing model to mass customization model, and to mass personalization model, which is the research object of this paper. Using the research method of system engineering, the system model, characteristic, technology, application blueprints, application scenarios, implementation paths of S-MMP from the perspective of top-level planning are studied. The complete system model of S-MMP proposed in this paper is in line with the development trend of today's industry and meets the urgent needs of enterprises, and it can provide theoretical guidance for enterprises in policy upgrading, model transformation, and business process reengineering. The search results of this paper can provide a reference value for companies to implement high-level planning of the smart system in manufacturing with mass personalization. [ABSTRACT FROM AUTHOR]

There is a recognized need for mass personalization for sustainability at scale. Mass personalization is becoming a leading research trend in the latest Industrial Revolution, whereas substantial research has been undertaken on the role of Industry 4.0 enabling technologies. The world is moving beyond mass customization, while manufacturing has led to mass personalization ahead of other industries. However, most studies have not treated human capabilities, machines, and technologies as sustainable collaboration. This research investigates mass personalization as a common goal under the latest Industrial revolutions. Also, it proposes a Reference Architecture Model for achieving mass personalization that contributes to understanding how Industry 5.0 enhances Industry 4.0 for higher resilience and sustainability through a human-centric approach. The study implies that Human Capital 5.0 leads collaboration with machines and technologies, bringing more value-added and sustainable products. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to analyze the mediating role of Supply Chain Flexibility on the interrelationships binding Lean Production implementation, Mass Personalization and business performance. Design/methodology/approach: A random sample of 260 companies obtained from a population of 1,717 Spanish companies that occupy an intermediate position in the supply chain has been used to test the proposed hypothetical framework. Telephone surveys using a computerized system have been used to collect data, obtaining a response rate of 15.6 and a structural equation model has been designed to test the six proposed hypotheses. Findings: Companies initially implement Lean Production to optimize Mass Personalization processes and improve business performance. However, in the presence of Supply Chain Flexibility, Lean Production implementation no longer has a direct impact on Mass Personalization and business performance, but it does have an indirect impact through the flexibility it achieves (shown as a total mediating path). Therefore, companies should implement Lean Production to achieve flexibility and thus optimize the Mass Personalization processes and obtain better performance. Originality/value: Academics and business managers may have supporting evidence on the role played by the total mediating effect of Supply Chain Flexibility on the relationship between Lean Production, Mass Personalization and business performance. A better knowledge of these management resources and their relationship could affect the way researchers and practitioners approach them, becoming more aware of the important role of the supply chain in competitiveness. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering 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.)

Researchers of the Mass Customization domain face not only challenges of proper and timeless identification of latest practical trends, but also difficulties in rational analyses on the numerous existing scientific studies in this field as well as a need for a comprehensive and multidimensional state-of-the-art overview of the Mass Customization research domain in the last three decades. Therefore, the present research article aims to provide a critical standpoint and reveal the main research directions and content at systemic, bibliometric and historical research levels in the period of 1990-2020. Four types of bibliometric clustering techniques and a visualization of results in a format of two-dimensional maps by the VOSviewer software were applied in the analysis on 1783 scientific papers from the Clarivate Analytics Web of Science Core Collection. The analysis reveals six historical periods in the Mass Customization research domain, from which, in the last three decades, three are identified as influencing modern Mass Customization research areas and objects. Results confirmed a shift from a stand-alone scientific approach to the customization of tangible products in the manufacturing field and their risk management, to a hybrid scientific approach with a focus on the customization of non-tangible products and personalized customer behavior in online environments. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering 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.)

Copyright of Technisches Messen is the property of De Gruyter 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.)

Purpose: This paper aims to explore the current state of research on supply chain flexibility (SCF) and mass personalization (MP) to identify the literature findings to date, research gaps and to provide guidelines for future research in this area. Design/methodology/approach: A systematic literature review of 64 papers was undertaken to address the use of SCF as a productive response to MP environments. The methodology used is made up of five steps: formulation of the research questions, identification of studies, selection and evaluation of studies, analysis and synthesis and presentation of the results. Findings: Three main research topics have been identified: personalization levels and flexible processes in supply chain, where flexible processes in supply chain are analysed as a productive response to high levels of MP; supply chain collaborative processes for SCF and MP, where product co-creation and relationships between supply chain members is analysed; and SCF and MP enabling technologies, in which technologies to support MP implementation and SCF are considered. Each of these three main topics have been divided into research lines and research sublines that allowed identifying a positive relationship between the SCF and the MP strategies. Research limitations/implications: Systematic literature review is a methodology reliable and recommended by a large number of scientific papers. However, it depends on available and accessible research studies and the researcher's criteria. The selection of certain criteria for inclusion and exclusion of papers introduces publication bias, which should be considered an intrinsic limitation to systematic literature review. Originality/value: The main literature findings in each research line and subline related to the SCF-MP relationship are identified and analysed. Furthermore, research gaps and further research lines in the SCF-MP area are highlighted. The information presented in this paper improves the literature on the advances in the SCF use as a productive response to MP environments. [ABSTRACT FROM AUTHOR]

Growing environmental awareness in society increasingly influences individual everyday decisions, such as which product to buy or how to sustainably use it. Yet, available information to support these decisions is often limited, or difficult to understand particularly regarding sustainability. Effective ways of communicating environmental impacts of individual decisions are required to close this gap. While Life Cycle Assessment (LCA) is an established tool to evaluate environmental impacts of products and services and support environmental decision-making, the results are typically standardized and based on statistical or averaged data. However, for individuals, this information might be irrelevant, as it neglects personal situation, behavior, information need, or individual level of expertise. In tackling those central issues of personalization in LCA, this article focuses on two main questions: How can individual aspects be addressed in LCA and at which stages of the methodology can LCA be personalized? For this purpose, the ISO 14040/44 standards are analyzed regarding individuality, and current approaches in literature are presented. In an explorative approach, this research identifies two general approaches of personalizing LCA. A personalized Life Cycle Inventory (LCI) enables evaluating the environmental impacts of personal(ized) products and conditions. A broader personalization approach based on the flexibility of the methodological framework of LCA aims at providing understandable and relevant results for individual stakeholders. This article provides an overview, outlines key aspects of this vision, and points out further research needs to bring the concept into application. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering 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.)

Graphical models are widely used to model the statistical relationships among variables in a system. Existing graphical models can be used to model the relationships among scalar variables, but cannot be directly applied to model a system with functional variables. In this paper, a novel functional graphical model is proposed to model complex systems where functional variables are measured. To cope with the small sample size problem, we further develop a special sparsity penalization approach to robustly learn the graphical model from limited sample size, and develop a difference from the mean penalization for functional variables. Simulation studies and a case study in a plasma spray manufacturing process are used to demonstrate the effectiveness of the proposed method.

Note to Practitioners—Emerging sensing and information technologies have provided unprecedented functional data collection capacity from systems over time. It is important and challenging to model the relationships among these variables. Among many different modeling alternatives, graphical models are powerful tools to characterize the underlying relationships among variables in systems. However, traditional graphical models cannot directly model a system with a mixture of functional and scalar variables. The proposed model aims to address this challenge by proposing a functional graphical model. Based on simulation studies and a case study for a plasma spray manufacturing process, it is shown that the proposed method performs well under various conditions. [ABSTRACT FROM PUBLISHER]

Purpose: In this paper, the authors aim to address the potential of mass personalization for ceramic tableware objects. They argue that additive manufacturing (AM) is the most adequate approach to the production of such objects. Design/methodology/approach: The authors review the manufacturing of ceramic tableware objects, both traditional techniques and AM processes, and assess which available AM technologies are suitable for the research purpose. Findings: The authors consider binder jetting and material extrusion as the most suitable processes for the production of ceramic objects to be integrated into a mass personalization system of ceramic tableware. Originality/value: This paper provides an original overview of traditional and innovative techniques in ceramic manufacturing, exposing not only its differences but also its commonalities. Such overview supports the conceptual design of original equipment. [ABSTRACT FROM AUTHOR]

Personalized healthcare, which uses individual characteristics to better predict and prevent disease and customize therapies, is a potential solution to our current healthcare crisis. Personalized care aims to improve quality of care and reduce overall healthcare costs. Despite its potential, adoption of personalized healthcare has been slow for several reasons, one of which is related to financial incentives toward change. This perspective piece discusses how the Affordable Care Act (ACA), through support for preventive care and comparative effectiveness research, begins to align the right incentives toward innovation around personalized risk prediction, innovation that is much needed as we aim to improve the health of individuals and communities. [ABSTRACT FROM AUTHOR]

The prevailing practice of design for mass customization manifests itself through a configure-to-order paradigm, which means to satisfy explicit customer needs (CNs) and built upon legacy design. With pervasive connectivity and interactivity of the Internet and sensor networks, personalization has been witnessed in a number of industry sectors as a promising strategy that makes the market of one a reality. Mass personalization entails a strategy of producing goods and services to satisfy individual customer's latent needs with values outperforming costs for both customers and producers. This review paper envisions an affective and cognitive design perspective to mass personalization. By exploiting implicit market demand information and revealing latent CNs, mass personalization aspires to assist customers in making better informed decisions, and to the largest extent, to anticipate customer satisfaction and adapt to customer delight. The key dimensions of mass personalization are identified and discussed. By capitalizing on user experience, affective and cognitive design for mass personalization is expected to address individual customer's latent CNs. The decisions of affective and cognitive design, involving affective and cognitive needs elicitation, affective and cognitive analysis, and affective and cognitive fulfillment, are reviewed with a wide range of interests, including engineering design, human factors and ergonomics, engineering psychology, marketing, and human-computer interaction. Recent trends and future research directions are also speculated to inspire more meaningful research in this area. [ABSTRACT FROM AUTHOR]

This paper presents customer participating 3D garment design methods for mass personalization. Complex fashion design is separated into garment surface modeling, pattern designing and texture mapping. Based on the modularization of the garment, we propose a component option sheet to describe the Garment surface Style (GS). Customers can choose components flexibly to construct a basic GS fast. Individual GS can be further modeled by editing the contour curves. Thus, we encode contour curves to save GS information and construct a GS library. The user can drag a favorite GS onto a 3D mannequin model and recover it by decoding the contour curves as a prototype for individual surface design. The users can also draw or drag style curves freely on a 3D triangular garment surface to design individual 3D pattern styles. Total or partial style curves encoding/decoding methods are proposed to store the 3D Pattern Style (PS), and to form a library. Customers can also choose a favorite PS and decode them on another garment surface as a prototype for individual pattern design. Through flexible choices from the garment component library, GS library, PS library, and simply dragging or drawing of contour curves and style curves, customers can easily and conveniently participate in 3D garment design for mass personalization. [ABSTRACT FROM PUBLISHER]

Today, megatrends such as individualization, climate change, emissions, energy, and resource scarcity, urbanization, and human well-being, impact almost every aspect of people's lives. Transformative impacts on many sectors are inevitable, and manufacturing is not an exception. Many studies have investigated solutions that focus on diverse directions, with urban production being the focus of many research efforts and recent studies concentrating on Industry 4.0 and smart manufacturing technologies. This study investigated the integration of smart factory technologies with urban manufacturing as a solution for the aforementioned megatrends. A literature review on related fields, mass personalization, sustainable manufacturing, urban factory, and smart factory was conducted to analyze the benefits, challenges, and correlations. In addition, applications of smart factory technologies in urban production with several case studies are summarized from the literature review. The integration of smart factory technologies and urban manufacturing is proposed as the urban smart factory which has three major characteristics, human-centric, sustainable, and resilient. To the best of the author's knowledge, no such definition has been proposed before. Practitioners could use the conceptual definition of an urban smart factory presented in this study as a reference model for enhancement of urban production while academics could benefit from the mentioned future research directions. [ABSTRACT FROM AUTHOR]