Mass Customization Mode Research Articles

Joint optimization decision of service provider selection and CODP positioning based on mass customization in a cloud logistics environment

PurposeBy introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.Design/methodology/approachThis paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.Findings(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.Originality/valueThe originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Application of Digital Technology to the Construction of the Fashion Design System under Mass Customization Mode

The study aims to improve the efficiency of clothing production and make the clothing design diversified and flexible. First, the design under the mass customization mode (MCM) based on digital technology (DT) is studied. Second, the development direction of clothing production under MCM is discussed through the analysis of the current situation of clothing production. Finally, the prospect of clothing design and production under MCM is predicted. The results show that the application of DT to clothing design under MCM can make the style change flexibly in the design as needed and effectively improve the efficiency of clothing production. With the help of DT, manufacturing enterprises will increase their investment in clothing production under MCM in the next 5 years, and the consumption rate of consumers for the clothes under MCM will also increase sharply. And the profit made under the mode will be four times as that of the previous. This study provides a reference for the development of MCM and helps understand the MCM further. Finally, the simulation results of clothing design show that the clothing designed following DT is faster, more flexible, and diversified, and DT dominates the production scale of clothing production.

A Fuzzy Programming Model for Positioning Customer Order Decoupling Point Based on QFD in Logistics Service with Mass Customization

Mass customization logistics service mode provides a new way to maintain the sustainable cooperative relationship between customers and integrators. One of the key factors to maintain the sustainable development of logistics service supply chain under MC mode is to locate a suitable customer order decoupling point (CODP) location. This paper investigates the problem of CODP in the logistics service supply chain based on the fuzzy set theory under the mass customization mode. With the help of a fuzzy QFD method and a new service quality function that we constructed, this paper quantifies the quality of a logistics service when the LSI selects a different CODP. Then, the fuzzy set of the high-quality logistics service and the fuzzy set of the satisfactory delivery time are built. Based on those two new fuzzy sets, this paper builds a new fuzzy programming model on CODP positioning. The solving methods of this model under different conditions are given. Finally, the influence of some important parameters on the optimal CODP position is studied by sensitivity analysis on a specific numerical case.

Task Offloading Strategy of 6G Heterogeneous Edge-Cloud Computing Model considering Mass Customization Mode Collaborative Manufacturing Environment

With the continuous integration of cloud computing, edge computing, and Internet of things (IoT), various mobile applications will emerge in future 6G network. Driven by real-time response and low energy consumption requirements, mobile edge-cloud computing (MECC) will play an important role to improve user experience and reduce costs. However, due to the complexity of applications, the computing capacity of devices cannot meet the low-latency and low energy consumption requirement. Meanwhile, subject to the limited supplement of power and energy system, the heterogeneous multilayer mobile edge-cloud computing (HetMECC) is proposed to join cloud server, edge server, and terminal devices for data calculation and transmission. By dividing computing tasks, terminal applications can receive reliable and efficient computing services. The simulation results show that the proposed model can achieve the low-latency requirement of data calculation and transmission and improve the robustness of architecture.

Multiobjective Optimization Model of Production Planning in Cloud Manufacturing Based on TOPSIS Method with Combined Weights

Combined with the research of mass customization and cloud manufacturing mode, this paper discussed the production planning of mass customization enterprises in the context of cloud manufacturing in detail, analyzed the attribute index of manufacturing resource combination, and given a system considering the characteristics of batch production in mass customization and the decentralization of manufacturing resources in cloud manufacturing environment. Then, a multiobjective optimization model has been constructed according to the product delivery date, product cost, and product quality that customers care most about. The Pareto solution set of production plan has been obtained by using NSGA‐II algorithm. This paper established a six‐tier attribute index system evaluation model for the optimization of production planning scheme set of mass customization enterprises in cloud manufacturing environment. The weight coefficients of attribute indexes were calculated by combining subjective and objective weights with analytic hierarchy process (AHP) and entropy weight method. Finally, the combined weights calculated were applied to the improved TOPSIS method, and the optimal production planning scheme has been obtained by ranking. This paper validated the effectiveness and feasibility of the multiobjective model and NSGA‐II algorithm by the example of company A. The Pareto effective solution has been obtained by solving the model. Then the production plan set has been sorted synthetically according to the comprehensive evaluation model, and the optimal production plan has been obtained.

Supply chain scheduling optimization based on genetic particle swarm optimization algorithm

In order to optimize supply chain scheduling problem in mass customization mode, the mathematical programming of supply chain scheduling optimization problem is modelled. At the same time, model mapping is defined as a directed graph to facilitate the application of intelligent search algorithms. In addition, the features of genetic algorithm and particle swarm algorithm are introduced. Genetic algorithm has a strong global search capability, and particle swarm optimization algorithm has fast convergence speed. Therefore, the two algorithms are combined to construct a hybrid algorithm. Finally, the hybrid algorithm is used to solve the supply chain optimization scheduling problem model. Compared with other algorithms, the results show that the hybrid algorithm has better performance. The mathematical programming model used in this paper can be further extended and improved.

Service-Oriented Manufacturing Agility and Application Based Flexibility

Introduced flexibility index method to study service-oriented manufacturing enterprise agility. Analyzed agility needs and elements of service-oriented manufacturing enterprise: customer participation, manufacturing network, mass customization mode and information integration platform. According to CTRS(Cost, Time, Robustness and Suitability) norm defined elements flexibility index. Results show elements resource utilization factor has a significant effect of agility while the time dimension is weak. Enterprises can shorten manufacturing and R & D time and expand marketing channels to improve the overall agility.

Web3D-Based Product Design and Interactive Customization Technology

In mass customization mode, it was an inevitable trend that user custom products become really required through network. Aimed at the characteristics of the products display and Customization on the Internet, Web3D are used in developing Customization methods of products form, material and color. It was proved that the method could help to improve consumers’ ability to customize products interactive on internet, which can promote participation of the customers and enhance the competitive ability of the enterprises.

Study on Pricing Method of Residential Development Project Based on Housing Mass Customization

As a traditional mode, Mass Production in real estate development is having changed to Housing Mass Customization. It is considered that not only production formalization and demand personalization could be combined with well by HMC mode,but also the separation degree between housing supplies and housing demand could be decreased in a great extent. The traditional pricing methods ,such as market comparison approach ,discounted cash flow and cost approximation, are not suitable for determining the price of residential development project produced by housing mass customization mode. In the paper, market behavior of HMC project is analyzed, and it is found that forward contracts theory can be applied to determine the HMC project price. In the finial, an appropriate pricing method is put forward .

Study on Module Encoding Method Oriented Product Configuration Design

For the successful realization of product configuration design (PCD) in the condition of mass customization mode, the module encoding methods are studied. By analyzing the product structure model and the process of computer-aided PCD, all related information which is required for the module is decided. This paper proposes a scientific module encoding method suitable for PCD. It describes the geometric features of the modules, the interface relationships and the affiliations between modules. Further more, it introduces additional attribute codes used to evaluate product configuration. By this way the product information can be fully expressed in order to improve the efficiency of PCD.

An exploratory study of the general requirement representation model for product configuration in mass customization mode

Product customization has been recognized as an effective means to implement mass customization (MC). Aiming at the shortcomings of the current methods in information capturing and describing, the general requirement modeling method for product configuration in MC mode is proposed. The detailed definition of the general requirement concept is put forward from several angles, including the time dimension, space dimension, feature dimension, etc., and the requirement information cell (RIC) method which fits the description of the general requirement information for the MC domain is also presented. Then, the formalized expressive framework of the RIC is given and the general requirement hierarchical model and correlative model of MC based on RIC is discussed. According to the application result, the formalized describing method of general requirement for MC has effectively supported the reuse of domain knowledge in the requirement modeling process for product configuration, as well as improved the standardization and intelligence of requirement information expression. This method’s utility, flexibility, and reliability has been verified through its application to the development of practical products.

Technology and application of product evolutionary design based on configuration in mass customization mode

Product customization has been recognized as an effective means to implement mass cus-tomization (MC). A new theory and method for MC-oriented evolutionary design of configuration product is presented based on the study of developing law of evolutionary design in integrated envi-ronment, which focuses on the innovation and reuse properties of configuration product. The key technologies for general requirement modeling in quick response to customer requirement, multi-level stepwise configuration optimization driven by customer requirement and evolutionary deduction of product variable structure based on configuration association are thoroughly investigated. The suc-cessful application of the presented method in the development of real-life products demonstrates its utility, flexibility and robusticity.

Why variation reduction is not everything: a new paradigm for service operations

Highlights that one service industry in the USA ‐ health care ‐ has accepted high inherent rates of variation into its process designs. Notes that, increasingly, health care industry leaders recognize that elimination of unnecessary variation is a necessary, but not a sufficient, condition for producing quality professional services at reasonable costs. Using the innovation model of Boynton et al. (1993), identifies continuous improvement, rather than mass production, as the key step in the rationalization of what has been a craft industry and the ultimate objective of delivering health care in a mass customization mode. Claims, however, that it is not sufficient, because high levels of inherent variation will continue to exist and must be managed, even in the best of all possible worlds. Reviews the health care experience (in the context of that model) to suggest how service operations managers and researchers should conceptualize variation, and then discusses what that conceptualization of variation implies about how operations management should treat variation in its modelling and decision making.