Mass-customized Products Research Articles

Product line strategy and supply chain structures for mass customized production using 3D printing

We develop game-theoretical models to capture unique features: design freedom, natural flexibility, and quality distinction of 3D printing, and propose the customization degree and unique labour division for 3D-printed products. We investigate a manufacturer’s product line strategy with 3D printing. The manufacturer can offer single standardized products (strategy S), single 3D-printed products (strategy T), or both products (strategy L) to consumers through its retailer. We further explore how supply chain structures influence the manufacturer’s product line strategy. We find (i) the optimal customization degree of 3D-printed products is lower under strategy L than strategy T. (ii) When the development cost of 3D-printed products is low/relatively low/moderate/high and the utility from product fit is high/moderate/relatively low/low, the manufacturer adopts strategy L/T/L/S. (iii) The retailer expects the manufacturer to adopt strategy T or L. (iv) In the centralised supply chain, the manufacturer prefers strategy L to T when the development cost of 3D-printed products is low. Moreover, the centralised supply chain is inferior to the manufacturer when the utility from product fit is low under strategy T and when the marginal development cost is intermediate under strategy L. We provide managerial insights for designing mass-customized products and product lines using 3D printing.

PackMASNet: An information integration approach for quality inspection in industry 5.0

Industry 5.0 (I5.0) is increasingly governed by Operation Technology and Information Technology. It hosts Deep Learning (DL) solutions as a premier tool for the informatization of Quality Inspection (QI) of Mass Produced Products (MPP) and Mass Customized Products (MCP) at the on-premise edge devices. Besides, these ever-evolving MCPs in I5.0 require newer DL models to informatize customized quality parameters, mandating significant storage and computing resources, that is challenging to achieve at resource-constraint edge platform. This work proposes PackMASNet, a continual learning-based information integration scheme that sustainably incorporates the QI information of multiple MCPs in a single Deep Neural Network (DNN) under the following constraints: (i) resource-limited on-premise edge devices, (ii) no access to prior product data, and (iii) negligible deterioration of quality information of frequently manufactured MPPs. A lightweight Cosine-similarity threshold mechanism is incorporated to leverage the benefits of knowledge transfer (cloning) while avoiding its adverse impact in multi-varied MCPs. The scheme proposes DNN performance, storage, computation, data, and time efficient solutions for industries implementing the edge computing paradigm on I5.0. The efficacy of the proposed scheme is validated for the predictive QI of real-world use case in injection molding. The scheme preserves the frequently used information of MPP by 99.07%, saves computation cost by 132 times, reduces the DNN training time by 20.45%, and improves overall performance by 43.60% over the state-of-the-art schemes.

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.

One-of-a-kind products: Leveraging strict uniqueness in mass customization

This research examines product uniqueness in its most pure form—products that are literally one of a kind. It does so in mass customization (MC) settings where consumers configure their own products. Due to extremely large solution spaces that are typically available in MC, a specific product configured by a consumer is often one of a kind in that it has never been produced before. How might firms leverage such strict product uniqueness to enhance consumer value? A natural way of doing so is to simply inform consumers that the product they have configured is one of a kind—through a feedback message that is either present-oriented (e.g., “this specific product has never been produced before”) or future-oriented (e.g., “this product will remain one of a kind in perpetuity”). Evidence from five experiments, including a large-scale field experiment, shows that one-of-a-kind feedback can cause a substantial increase in consumers’ product valuation. This value-enhancing effect of one-of-a-kind feedback specifically occurs in product domains that are primarily matters of subjective taste. By contrast, such feedback tends to reduce consumers’ product valuation in domains that are primarily matters of objective quality. These findings advance our understanding of the concept of product uniqueness, and of how firms can harness the one-of-a-kindness of mass-customized products to unlock consumer value.

Toward a Plug-and-Work Reconfigurable Cobot

The ongoing trend from mass-produced to mass-customized products with batch sizes as small as a single unit has highlighted the need for highly adaptable robotic systems with lower downtime for maintenance. To address these demands, this article proposes the development of a novel reconfigurable collaborative robot (cobot), which has the potential to open up many new scenarios within the rapidly emerging flexible manufacturing environments. As the technological contribution, we present a complete hard- and software architecture for a quickly reconfigurable EtherCAT-based robot. This novel approach allows to automatically reconstruct the topology of different robot structures, composed of a set of body modules, each of which represents an EtherCAT slave. As the theoretical contribution, we propose a method to obtain in an automatic way the kinematic and dynamic model of the robot and store it in universal robot description format (URDF) as soon as the physical robot is assembled or reconfigured. The method also automatically reshapes a generic optimization-based controller to be instantly used after reconfiguration. While this article focuses on reconfigurable manipulators, the proposed concept can support arbitrary serial kinematic tree-like configurations. We demonstrate the contributions with examples of the following: how the topology of the robot is reconstructed and the URDF model is generated, and a Cartesian task application for a cobot built with the basic modules, demonstrating the quick reconfigurabilty of the system from a 4-degrees-of-freedom (DOF) robot to a 5-DOF robot, in order to satisfy new workspace requirements.

Is Adopting Mass Customization a Path to Environmentally Sustainable Fashion?

Problem definition: In high-product-variety businesses like fashion, mass production (MP) systems create environmental waste in the form of overproduction on a colossal scale. Mass customization (MC) has been proposed—without solid evidence—as a solution. In this paper, we analyze whether MC can indeed offer a win-win solution that helps both the bottom line and the environment. We also study the impact of three real policy options: promoting MC, charging a disposal fee for overproduction, and recycling. Academic/practical relevance: There is increasing interest in mass-customizing fashion goods, not only because consumers value customization, but also because MC is perceived to be environmentally friendly. Our paper puts this advocacy for MC to the test. We contribute to the literature, which has been largely silent on the issue, by uncovering when MC offers a win-win and relating such market outcomes to policy ideas. Methodology: We develop an analytical model of an MP firm adopting MC (going hybrid). The firm’s profit-maximizing variety, price, and inventory decisions then form the basis of our understanding the environmental impact of adopting MC and assessing various policy options. Results: Adopting MC can be a win-win, but it can also increase overproduction and hurt the environment. Our policy analyses reveal two kinds of insights. The first kind is about whether a policy expands win-win outcomes—encouraging sustainable adoption of MC. Among the policy ideas we explore, only promoting MC so as to increase consumers’ tolerance for waiting for mass-customized products can do that unambiguously. The second kind of insight is about whether a policy reduces the hybrid firm’s environmental impact. Only a disposal fee and costly recycling programs can do that unambiguously. Managerial implications: For MC adoption to be a win-win, policy makers must (1) work on convincing consumers to wait for bespoke fashion; (2) target MP firms with low cost of variety (high product-mix flexibility) with disposal fees or costly recycling programs; and (3) encourage those with relatively higher cost of variety to develop/acquire technology that would make recycling profitable. History: This paper has been accepted for the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations Management. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1088 .

Process Planning, Scheduling, and Layout Optimization for Multi-Unit Mass-Customized Products in Sustainable Reconfigurable Manufacturing System

Currently, manufacturers seek to provide customized and sustainable products, requiring flexible manufacturing systems and advanced production management to cope with customization complexity and improve environmental performance. The reconfigurable manufacturing system (RMS) is expected to provide cost-effective customization in high responsiveness. However, reconfiguration optimization to produce sustainable mass-customized products in RMS is a complex problem requiring multi-criteria decision making. It is related to three problems, process planning, scheduling, and layout optimization, which should be integrated to optimize the RMS performance. This paper aims at integrating the above three problems and developing an effective approach to solving them concurrently. It formulates a multi-objective mathematical model simultaneously optimizing process planning, job-shop scheduling, and open-field layout problem to improve RMS sustainability. The penalty for product tardiness, the total manufacturing cost, the hazardous waste, and the greenhouse gases emissions are minimized. Economic and environmental indicators are defined to modify the Pareto efficiency when searching the Pareto-optimal solutions. Exact Pareto-optimal solutions are obtained by brute-force search and compared with those of the non-environmental indicator model. NSGA-III is adopted to obtain the approximate Pareto-optimal solutions in high effectiveness and efficiency. A small numerical example is applied to validate the mathematical model and resolution methods.

Deep learning-based visual control assistant for assembly in Industry 4.0

Product assembly is a crucial process in manufacturing plants. In Industry 4.0, the offer of mass-customized products is expanded, thereby increasing the complexity of the assembling phase. This implies that operators should pay close attention to small details, potentially resulting in errors during the manufacturing process owing to its high level of complexity. To mitigate this, we propose a novel architecture that evaluates the activities of an operator during manual assembly in a production cell so that errors in the manufacturing process can be identified, thus avoiding low quality in the final product and reducing rework and waste of raw materials or time. To perform this assessment, it is necessary to use state-of-the-art computer vision techniques, such as deep learning, so that tools, components, and actions may be identified by visual control systems. We develop a deep-learning-based visual control assembly assistant that enables real-time evaluation of the activities in the assembly process so that errors can be identified. A general-use language is developed to describe the actions in assembly processes, which can also be used independently of the proposed architecture. Finally, we generate two datasets with annotated data to be fed to the deep learning methods, the first for the recognition of tools and accessories and the second for the identification of basic actions in manufacturing processes. To validate the proposed method, a set of experiments are conducted, and high accuracy is obtained.

An integrated approach to optimize the configuration of mass-customized products and reconfigurable manufacturing systems

The current global unpredictable market is characterized by increasing demand for highly customized products. To thrive in this scenario, it becomes essential to establish a closer interaction between product and manufacturing system, keeping the main focus on the client. Modular product design (MPD) is the best strategy to produce a large product variety. MPD’s configuration phase represents a key step for mass customization because it allows customers to be integrated into the value-creation process. Reconfigurable manufacturing systems (RMS) seem to be the most appropriate manufacturing system to manufacture mass-customized products due to their ability to be quickly reconfigured, adjusting their production capacity and functionality to fit new market demands. Aiming to integrate individual customer needs with product and manufacturing decisions, this paper proposes a new 0-1 nonlinear integer programming model to concurrently optimize the configuration of modular products and RMS (including machine and layout configuration levels), driven by individual customer requirements. A genetic algorithm-based approach is proposed to solve this model, and its parameters are tuned with a 2-full factorial design. An example of customizable office chairs is used to illustrate the proposition, and different scenarios of customer requirements and RMS configurations were presented. Results evidence that varying initial machines’ configurations can highly affect the process plan and the overall manufacturing costs; however, there is no evidence that changes in initial layout configurations cause significant effects. In summary, this work confirms the relevance of integrating modular product and RMS configuration decisions for minimizing costs of producing highly mass-customized products.

Concurrent optimisation of modular product and Reconfigurable Manufacturing System configuration: a customer-oriented offer for mass customisation

ABSTRACT Reconfigurable Manufacturing Systems (RMS) emerged from companies’ needs to increase their responsiveness to an uncertain market, in which customers are increasingly demanding mass-customised products. Companies focused on mass customisation mainly use the modular product design (MPD) strategy to cost-effectively provide a large product variety. Hence, coupling the MPD with the manufacturing in RMS seems to be a good strategy to effectively provide mass-customised products with lower costs. However, few papers have concurrently optimised the modular products’ and RMS’s configurations for that end. Further, very few papers have explored the RMS’s layout configuration. In order to fill these gaps, this paper proposes a Nonlinear Integer Programming model that integrates the configuration of modular products and RMS, driven by individual customer requirements, to minimise manufacturing costs of mass-customised products. An approach combining a Modified Brute-Force Algorithm (MBFA) and a genetic algorithm (GA) is proposed and compared with a CPLEX-based approach for a small-sized problem, proving its ability to find an optimal solution in lower computation time. An illustrative example of modular smartphones confirms the MBFA-GA’s ability to solve medium/large-sized problems in a reasonable amount of time while ensuring an optimal product configuration that meets customer requirements.

The effect of gender on willingness to pay for mass customised running shoes

ABSTRACT We investigate whether gender and different levels of customisation have a significant effect on consumers’ willingness to purchase mass customised running shoes. An online panel survey was utilised to collect data from 353 Australian adults who wear running shoes at least once a month. Three attributes – degree of customisation, price, and delivery time were utilised in the data analysis to explore willingness to pay for customised shoes. Informed by conjoint analysis and t-tests, the study makes a significant theoretical contribution by extending the understanding of inconveniences of mass customisation from the perspective of customers’ willingness across genders. It is found that for women, degree of customisation and delivery time are the most important attributes, while for men, price and degree of customisation are the more crucial attributes. Female customers are more willing to purchase the product than male customers. The study addresses the research gap that is how differently females and males who usually have different sensory perceptions respond to mass-customised products. Further, the study provides valuable strategic insights for both manufacturers and marketers to cater fragmented consumer markets through mass customisation by identifying subtle differences in customer readiness among their target group of customers.

Is Adopting Mass Customization a Path to Environmentally Sustainable Fashion?

Problem definition: In high-product-variety businesses like fashion, mass production (MP) systems create environmental waste in the form of overproduction on a colossal scale. Mass customization (MC) has been proposed -- without solid evidence -- as a solution. In this paper, we analyze whether MC can indeed offer a win-win solution that helps both the bottom line and the environment. We also study the impact of three real policy options: promoting MC, charging a disposal fee for overproduction, and recycling. Academic/practical relevance: There is increasing interest in mass-customizing fashion goods, not only because consumers value customization, but also because MC is perceived to be environmentally friendly. Our paper puts this advocacy for MC to test. We contribute to the literature, which has been largely silent on the issue, by uncovering when MC offers a win-win and relating such market outcomes to policy ideas. Methodology: We develop an analytical model of an MP firm adopting MC (going hybrid). The firm’s profit-maximizing variety, price and inventory decisions then form the basis of our understanding the environmental impact of adopting MC and assessing various policy options. Results: Adopting MC can be a win-win, but it can also increase overproduction and hurt the environment. Our policy analyses reveal two kinds of insights. First kind is about whether a policy expands win-win outcomes -- encouraging sustainable adoption of MC. Among the policy ideas we explore, only promoting MC so as to increase consumers' tolerance for waiting for mass-customized products can do that unambiguously. Second kind of insight is about whether a policy reduces the hybrid firm's environmental impact. Only disposal fee and costly recycling programs can do that unambiguously. Managerial implications: For MC adoption to be a win-win, policy makers must (1) work on convincing consumers to wait for bespoke fashion, (2) target MP firms with low cost of variety (high product mix flexibility) with disposal fees or costly recycling programs, and (3) encourage those with relatively higher cost of variety to develop/acquire technology that would make recycling profitable.

Consumer Response to Aesthetic Mass Customization

Although recent research has explored consumers’ reactions towards mass customization (MC) in general, these studies have considered aesthetic and functional MC as one and the same. In the present article, we focus specifically on consumer response to aesthetic MC because there are some unique factors that influence this type of MC. Providing insights in these factors can help firms in order to more successfully implement aesthetic MC strategies in products. In our research, hypothetical MC configurators were presented to respondents. The configurators were varied and allowed for different extents of aesthetic MC. In addition, the visibility of the mass-customized product elements to others was manipulated. Our findings suggest that customizing a product’s aesthetic features enhances its self-expressive value, which on its turn positively affects consumers’ evaluations of MC and the behavioural intentions (e.g., purchase intention). Furthermore, a greater extent of aesthetic MC increases the perceived complexity of the MC task, which negatively affects evaluation. Finally, visibility of the mass-customized product elements to others enhances the self-expressive value of aesthetically customized products. The article concludes with the implications of these findings for firms interested in pursuing MC strategies.

Self-monitoring tendency and fashion involvement: Antecedents and consequences of perceived relative value of mass-customized fashion products in a gift-giving context

ABSTRACTThe process of mass customizing a product online hugely eclipses with that of gift selection due to similarity in nature of both the processes where one would devote considerable time, effort, and financial resources as well as cognitive and/or emotional factors. Using the integrated Stimulus-Organism-Response (S-O-R) paradigm, this study aims to shed light on the impact of gift-givers’ personal traits on their value perceptions of and attitude toward gifting online mass-customized fashion products to their close family and friends. Using a quantitative approach and a purposive sample, usable responses from 388 Generation Z consumers were obtained. Structural equation modeling results demonstrated that gift-givers’ personal traits had significant impacts on their perception of mass-customized fashion product attributes as well as value perception of such products and, in turn, had an indirect impact on attitude toward purchasing such products as a gift for friends and family. We found that perceived salience of products attributes had the largest impact on the perceived relative value of mass-customized fashion products, which, in turn, positively influence their attitude toward giving online mass-customized fashion products to close family and friends.

Parametric Topology Optimization Toward Rational Design and Efficient Prefabrication for Additive Manufacturing

The significant advance in the boosted fabrication speed and printing resolution of additive manufacturing (AM) technology has considerably increased the capability of achieving product designs with high geometric complexity and provided tremendous potential for mass customization. However, it is also because of geometric complexity and large quantity of mass-customized products that the prefabrication (layer slicing, path planning, and support generation) is becoming the bottleneck of the AM process due to the ever-increasing computational cost. In this paper, the authors devise an integrated computational framework by synthesizing the parametric level set-based topology optimization method with the stereolithography (SLA)-based AM process for intelligent design and manufacturing of multiscale structures. The topology of the design is optimized with a distance-regularized parametric level set method considering the prefabrication computation. With the proposed framework, the structural topology optimization not only can create single material structure designs but also can generate multiscale, multimaterial structures, offering the flexibility and robustness of the structural design that the conventional methods could not provide. The output of the framework is a set of mask images that can be directly used in the AM process. The proposed approach seamlessly integrates the rational design and manufacturing to reduce the numerical complexity of the computationally expensive prefabrication process. More specifically, the prefabrication-friendly design and optimization procedure are devised to drastically eliminate the redundant computations in the traditional framework. Two test examples, including a free-form 3D cantilever beam and a multiscale meta-structure, are utilized to demonstrate the performance of the proposed approach. Both the simulation and experimental results verified that the new rational design could significantly reduce the prefabrication computation cost without affecting the original design intent or sacrificing the original functionality.

Yığın Kişiselleştirme Yaklaşımı Ve Örnek Uygulama - Mass Customization And Sample Application

Unpredictable demand, heterogeneous customer requests, short product life cycles, increase in the demand for customized and quality product and services and technological and innovative discoveries that enable all these have boosted the rivalry between enterprises. The role of mass customization system in defining and meeting the requests and necessities of the customers who are the focal point of this rivalry in an efficient and adequate manner has increased since 1980’s. Mass customization means offering products that meet the requirements and the necessities of the customers at mass production costs. Mass customization system which provides for the customer participation at different points of product value chain provides the opportunity to customize products in different levels. In the kitchen production industry where design-production-assembly and distribution stages of the production are completely determined according to the specifications of the product which is going to be presented to the customer, mass customized products provide cost advantages. Aim of this study is to be able to present the cost advantage by comparing the costs of Enterprise B which custom produces kitchens and Enterprise A which produces modular kitchens with mass customization approach. To that end, cost data of the two enterprises analyzed and it was seen that the enterprise which uses mass customization production system gains cost advantage by using scale and scope economies efficiently.

Developing complex, mass-customized products in SME networks: Perspectives from co-creation, solution space development, and information system design

Developing complex, mass-customized products in SME networks: Perspectives from co-creation, solution space development, and information system design

Roadmap to 3D-Printed Oral Pharmaceutical Dosage Forms: Feedstock Filament Properties and Characterization for Fused Deposition Modeling

Application of additive manufacturing techniques (3D printing) for mass-customized products has boomed in the recent years. In pharmaceutical industry and research, the interest has grown particularly with the future scenario of more personalized medicinal products. Understanding a broad range of material properties and process behavior of the drug-excipient combinations is necessary for successful 3D printing of dosage forms. This commentary reviews recent 3D-printing studies by fused deposition modeling (FDM) technique in pharmaceutical sciences, extending into the fields of polymer processing and rapid prototyping, where more in-depth studies on the feedstock material properties, modeling, and simulation of the FDM process have been performed. A case study of a model oral dosage form from custom-prepared indomethacin-polycaprolactone feedstock filament was used as an example in the pharmaceutical context. The printability was assessed in the different process steps: preparation of customized filaments for FDM, filament feeding, deposition, and solidification. These were linked with the rheological, thermal, and mechanical properties and their characterization, relevant for understanding the printability of drug products by FDM.

What determines firms’ intention to postpone product differentiation?

In present-day Japan, more firms are beginning to apply postponed product differentiation in favor of providing mass-customized products. Mass customization can lead to competitive advantages in satisfying consumers’ individual needs. We propose a causal model to describe why and how Japanese distributors decide to postpone product differentiation and supply mass-customized products. The model was empirically tested by structural equation modeling with a dataset from Japanese automobile dealers, who have employed highly advanced mass customization systems and are world leaders in this practice. The results show that two environmental factors, uncertainty and innovation, affect firms’ expectations of their customers’ intentions to purchase mass-customized products and, in turn, firms’ decisions regarding postponing product differentiation in favor of mass customization. Mass customization has a high potential for growth in the future due to increasing levels of uncertainty and evolving forms of innovation.

Australian customer willingness to pay and wait for mass-customised products

PurposeThe purpose of this paper is to find out how consumers constantly trade off the potential extra cost of mass customisation with the additional time they have to wait to receive their customised products.Design/methodology/approachThe authors examine this issue by using conjoint analysis to estimate the trade-offs using a sample of Australian consumers. The authors use cluster analysis to form market segments in the three product categories examined.FindingsThe segments demonstrate that there are groups of customers who are quite willing to trade-off price with waiting time. The results have significant implications for Australian manufacturers who are contemplating moving into mass customisation.Originality/valueMany researchers have investigated the issue of a customer’s readiness to buy a customised product. In particular, they have examined whether customers are willing to pay extra for a mass-customised product, whether they would spend some time to design it, as well as wait to receive it. There has been no study that has examined all three factors simultaneously. The results of this study can help manufacturers form a better understanding of customer willingness for purchasing mass-customised products.