Mass Customization Environment Research Articles

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.

Using Transfer Learning to Reduce Preparing Time of Online Diagnosis with Limited Rotating-Component Data

Under the environment of mass-customization, valid samples for a specific target object become fewer and fewer. Thus, Transfer Learning (TL) is widely applied to those data-consuming Deep Learning (DL) and Machine Learning (ML) models to avoid recollecting high-volume training samples from scratch. However, TL-based methods used in fault diagnosis for mechanical rotating components are still in the infancy phase. Poor practicality and usability problems increase the total preparing time. Without online diagnosis, there might be more unknown risks during the preparing time of a TL method. To reduce the preparing time of existing TL techniques, this paper proposes a TL-based Gradual Improvement Scheme (TLGIS) to achieve a systematic online diagnosis of rotating components. TLGIS solves the problem through seamless interactions among five modules of Data Preprocessing (DP), Data Estimating (DE), Data Modeling (DM), Model Improving (MI), and Accuracy Checking, (AC). Via illustrative examples, TLGIS is demonstrated to be reliable and robust using deep Convolutional Neural Networks (CNN) by two public bearing datasets from the Internet and two types of rotating wheel datasets from a practical CNC machine. In total, TLGIS only requires at least 80 samples and at most 250 samples divided into small-size batches to gradually and continuously fine-tune the model with an accuracy of 90% and 99%, respectively, instead of inputting a large-scale dataset all at once, which is unrealistic in a practical production scenario. Compared to conventional approaches, TLGIS efficiently saves at most 90% of preparing time.

The role of manufacturing efficiency in the achievement of sustainable mass customization 4.0

ABSTRACT One of the goals of the Industry 4.0 paradigm is the sustainable success within a mass customization environment, which in turn, depends on the manufacturing efficiency of the transformation processes. In this paper we propose to represent manufacturing efficiency within the context demand fulfillment. The main original contribution of this paper are two demand fulfillment analytical expressions. Their novelty is on the way they are expressed, that is, in terms of the structural elements that define a mass customization environment. Their usefulness was put to the test via a Discrete Event Simulation (DES) model of two different demand fulfillment strategies (namely inventory-oriented level and capacity-oriented chase strategies). The obtained results suggest that the analytical expressions act as a fairly good trend indicator of the missed demand values increase/decrease. A discussion of the managerial implications of these findings are presented at the end of this document.

Towards the Development of a Digital Twin for a Sustainable Mass Customization 4.0 Environment: A Literature Review of Relevant Concepts

Digital Twins (DTs) are one of the disruptive technologies associated with the Industry 4.0 concept. A DT connects the physical manufacturing system with the digital cyberspace, via the synchronization of the simulation (i.e., physical configurations) and data models (i.e., product, process, and resource models) of the manufacturing system. This synchronization of both worlds—the physical and digital—allows one to address the issue of manufacturing customized products. This challenge of mass customization (1) puts forward the goal of achieving the highest level of customer satisfaction, and (2) creates the need for the optimization of the complete value creation process. Within an Industry 4.0 context, the latter is translated as the interlinking of production resources and systems, via a DT, as it is in the physical world where the actual value-creation process takes place. The success of an Industry 4.0 mass customization environment (or mass customization 4.0), depends on its degree/level of sustainability. For these reasons, the present paper presents a review of relevant concepts related to the role of DTs in the achievement of a mass customization 4.0 environment, plus some proposals of how to address the identified research challenges. A future research agenda is proposed at the end of the paper.

Production Scheduling of Personalized Fashion Goods in a Mass Customization Environment

The COVID-19 pandemic has put fashion manufacturers’ needs for optimization in the spotlight. This study argues that mass customization is becoming increasingly instrumental for offering consumers individualized solutions and that suppliers of fashion have to look for more sophisticated solutions in order to face the increasing demand for more sustainable products. With the deduction of a mathematical model derived from production sequencing it became evident that sustainability can be associated with a level production schedule and that cost-based production optimization is useful in achieving holistic sustainability in the fashion industry. The flexibility in the conceived mathematical model specifications allows for a generalizable approach, not limited to a single branch of the fashion industry. This paper additionally delivers a cost-based optimization approach which fashion companies, operating in a mass customization production layout, can easily implement without extensive know-how. The proposed two-stage algorithm is based on the concept of level scheduling. In a first stage, the algorithm determines a feasible production sequence in a time-efficient way while, in the second stage, it further advances the efficiency of the solution. Thus, it offers a framework to optimize a production in a mass customization environment and can contribute to a company taking major steps towards a holistic sustainable orientation as available resources are used more (cost) efficiently.

Applying the fundamentals of TPS to realize a resilient and responsive manufacturing system

Concepts like the Toyota Production System (TPS) and Quick Response Manufacturing (QRM) are often presented as alternative manufacturing methods or strategies suited for different manufacturing conditions. QRM is depicted as a Job-shop alternative (low volume-high mix) to TPS, and TPS is viewed as a method best suited for high volume-low mix environments. However, the realities of manufacturing organizations today are that they operate in a mass-customization environment with high total volumes to achieve economies of scale, and high variability due to the widening of choices available to customers. Which means that manufacturers must produce an infinite number of variants to serve individual customer needs, on a limited number of production lines, emphasising the need for both efficiency and responsiveness. In this paper we present preliminary findings from two Norwegian manufacturing companies who are applying the concepts of TPS to realize a resilient and responsive manufacturing system through a process of action learning. Instead of rigidly adopting the best practices developed by others, the companies are building flexible manufacturing systems through discovering their own paths towards improved quality, greater flexibility, and shorter lead-times - by finding and facing their challenges and engaging everyone in forming solutions, together.

A case study on the integration of assembly line balancing and feeding decisions

Mass-customization of products imposes new challenges on the planning of assembly lines due to an increased number of product models and a large variety of parts. Traditionally, both academics and practitioners approached the planning of an assembly line by balancing the assembly line, i.e., assigning tasks to stations, and decided on line feeding policies based on this outcome. However, this approach neglects the reciprocal effects between the two decision-making outcomes, i.e., the impact of line feeding decisions on task times and the impact of balancing decisions on feeding requirements and constraints. This interaction is of peculiar interest for assembly lines in a mass-customization environment due to the large number of assembly tasks and parts. Therefore, this study describes a framework that simultaneously optimizes both problems and minimizes overall costs. We show preliminary results using real-world data from a large automotive company.

A Hybrid Knowledge-Based Recommender for Product-Service Systems Mass Customization

Manufacturers today compete to offer not only products, but products accompanied by services, which are referred to as product-service systems (PSSs). PSS mass customization is defined as the production of products and services to meet the needs of individual customers with near-mass-production efficiency. In the context of the PSS mass customization environment, customers are overwhelmed by a plethora of previously customized PSS variants. As a result, finding a PSS variant that is precisely aligned with the customer’s needs is a cognitive task that customers will be unable to manage effectively. In this paper, we propose a hybrid knowledge-based recommender system that assists customers in selecting previously customized PSS variants from a wide range of available ones. The recommender system (RS) utilizes ontologies for capturing customer requirements, as well as product-service and production-related knowledge. The RS follows a hybrid recommendation approach, in which the problem of selecting previously customized PSS variants is encoded as a constraint satisfaction problem (CSP), to filter out PSS variants that do not satisfy customer needs, and then uses a weighted utility function to rank the remaining PSS variants. Finally, the RS offers a list of ranked PSS variants that can be scrutinized by the customer. In this study, the proposed recommendation approach was applied to a real-life large-scale case study in the domain of laser machines. To ensure the applicability of the proposed RS, a web-based prototype system has been developed, realizing all the modules of the proposed RS.

An Entropy-Based Formulation for the Support of Sustainable Mass Customization 4.0

Industry 4.0, an information and communication umbrella of terms that includes the Internet of Things (IoT) and cyber-physical systems, aims to ensure the future of the manufacturing industry competing in a proper environment of mass customization: demand for short delivery time, high quality, and small-lot products. Within this context of an Industry 4.0 mass customization environment, success depends on its sustainability, where the latter can only be achieved by the manufacturing efficiency of the smart factory-based Industry 4.0 transforming processes. Even though Industry 4.0 is associated with an optimal resource and energy productivity/efficiency, it becomes necessary to answer if the integration of Industry 4.0 elements (like CPS) has a favorable sustainability payoff. This requires performing energy consumption what-if analyses. The original contribution of this paper is the use of the entropy-based formulation as an alternative way of performing the initial steps of the energy consumption what-if analyses. The usefulness of the proposed approach is demonstrated by comparing the results of a discrete-event simulation model of mass customization 4.0 environment and the values obtained by using the entropy-based formulation. The obtained results suggest that the entropy-based formulation acts as a fairly good trend indicator of the system’s performance parameters increase/decrease. The managerial implications of these findings are presented at the end of this document.

Quality monitoring by special charts for highly customized production systems

This study presents alternative specials control charts formulation to deal with the flexibility in the quality features due to a mass customization production system. The proposed charts have capacity to detect small shifts from process target faster than traditional approaches for flexible systems, thus improving the quality monitoring process. The proposed charts have been compared with other conventional charts using simulation scenarios generated from Monte Carlo experimentation. Results show that the proposed EWMA chart for flexible systems is the most robust among the evaluated control charts to apply in Mass Customization environment. The performance of the best chart was analyzed in a flexible process and managerial implications were discussed.

Research on the Functional Design of Reconfigurable Manufacturing System Under Mass Customization Environment

Firstly, clarify the background of the reconfigurable manufacturing system and the axiomatic design theory, axiomatic design has two axioms including independent axiom and information axiom. This paper is based on Axiomatic Design, Using the independent axiom to the function design of the reconfigurable manufacturing system, the overall goal of three-level decomposition, each level of decomposition will list the corresponding design matrix to verify whether it meets the independence, and then summarizes the integrity of the decomposition of the design, finally, the feasibility of the design scheme is verified by an example.

Arquitectura para la previsión, planificación y reaprovisionamiento colaborativo en un entorno de personalización en masa

En este trabajo se propone una arquitectura para la previsión, planificación y reaprovisionamiento colaborativo en un entorno de personalización en masa. Para ello, se identifica las actividades principales de los modelos colaborativos más destacados y los procesos principales asociados a los entornos de personalización en masa. Para llegar a ésta, se proponen un conjunto de interfases asociados a la definición de productos y servicios adicionales, a la fabricación y expedición, así como a actividades de transporte y recepción. La propuesta se compone de un modelo conceptual, una metodología de implantación, así como por posibles soluciones tecnológicas asociadas para su desarrollo en empresas industriales.

Reducing Impact of Negative Complexity on Sustainability of Mass Customization

In the mass customization environment, product platform development includes several aspects. One relates to the extent to which products are customized. Usually, a high level of product variety brings significant benefits to customers. On the other hand, a high degree of product customization may have a negative environmental impact during production, due to higher material usage. One possible way to reduce the impact is eliminating infeasible configuration options, caused by incompatibilities between optional component types, within a product platform. Such optional components are a source of negative complexity. However, a reduction of optional component types within a product platform can lead to decreasing the extent of the variety of a product to an undesirable level. An effective way of finding this optimal level of reduction is to quantify and analyze the rates between positive and negative complexities, which are related to the numbers of configuration options. The method for this purpose is presented in this paper.

A Research on Optimization Method for Integrating Component Selection and Production Scheduling under Mass Customization

This paper proposes a method which is to achieve an optimal production scheduling and component selection simultaneously using an autonomous distributed technique under mass customization environment. The proposal method decides a production scheduling and component selection to aim minimizing the delay of acceptable due date. The proposal method uses a combinatorial auction for modelling negotiation between manufacturer and customers toward an optimal plan. Numerical examples are then discussed to demonstrate its suitability in obtaining an optimal plan under negotiations between manufacturer and customers.

Holonic supply chain: A study from family-based manufacturing perspective

In the contemporary business environment, to adhere to the need of the customers, caused the shift from mass production to mass-customization. This necessitates the supply chain (SC) to be effective flexible. The purpose of this paper is to seek flexibility through adoption of family-based dispatching rules under the influence of inventory system implemented at downstream echelons of an industrial supply chain network. We compared the family-based dispatching rules in existing literature under the purview of inventory system and information sharing within a supply chain network. The dispatching rules are compared for Average Flow Time performance, which is averaged over the three product families. The performance is measured using extensive discrete event simulation process. Given the various inventory related operational factors at downstream echelons, the present paper highlights the importance of strategically adopting appropriate family-based dispatching rule at the manufacturing end. In the environment of mass customization, it becomes imperative to adopt the family-based dispatching rule from the system wide SC perspective. This warrants the application of intra as well as inter-echelon information coordination. The holonic paradigm emerges in this research stream, amidst the holistic approach and the vital systemic approach. The present research shows its novelty in triplet. Firstly, it provides leverage to manager to strategically adopting a dispatching rule from the inventory system perspective. Secondly, the findings provide direction for the attenuation of adverse impact accruing from demand amplification (bullwhip effect) in the form of inventory levels by appropriately adopting family-based dispatching rule. Thirdly, the information environment is conceptualized under the paradigm of Koestler’s holonic theory.

A Mass Customization Information Systems Architecture Framework

Now that providing individual customization of products is an effective way to compete in the global economy, smart manufacturers are finding the way to overcome traditional mass production limitations. As the benefits of mass customization are realized through well designed information systems that provide direct links among value chain partners and integrate various business activities, the importance of information systems architecture in the delivery of customized goods can hardly be overemphasized. Drawing on concepts from the interrelated literature streams of organizational process-view, this paper examines the information systems requirements for mass customization and proposes an information system architecture framework for customized goods. This information systems architecture enables enterprise — wide integration, reduces systems complexity as well as the Bullwhip effect, and streamlines business processes in mass customization environment.

Key Technologies of the Customization Product CAD/CAE Integrated Analysis System

On the basis of scale-based modular product family design method, the customization product CAD/CAE integrated system was studied under mass customization environment. The system divides into three parts including programming, design and evaluating process. First of all, product family model was built during programming process, which includes functional model, principle model and structure model. Then based on the product family model database, in accordance with the theory of variant design, using parametric CAD re-development technology, specific product satisfied by client customizes rapidly. Finally utilizing finite element analysis to analyze and evaluate the customization design, the customization result will be more reasonable and high efficiency.

Research on Product Platform Innovation and Evolution Based on Lifecycle

To enhance the ability of product platform innovation and upgrading under Mass Customization (MC) environment, the concept of Product Platform Life Cycle (PPLC) was put forward. The innovation and evolving process and the characters of PPLC were analyzed. The Stability of the platform and its disturbance factors were discussed. A model which describes the process of product platform innovation and evolution was proposed. Then disturbance factors affecting product platform stability and platform innovation process were discussed.

Measuring the Costs of Custom Products through Better Technology Utilization

This case study details the process of determining the economic feasibility of implementing lean manufacturing in a small mass customization manufacturing company in the medical industry. The case study investigates the information required for a lean implementation and proposes a number of changes to the work procedures (including instrumentation) to obtain the data. A large number of enterprise resource planning systems were evaluated for their suitability to track data in the mass customization environment and the top candidates are compared in the article. The current labor and materials costs are estimated to determine the magnitude of potential savings to support the changes. Based on the analysis the recommended solution has a payback period of approximately two years.

Integrated Vehicle Configuration System—Connecting the domains of mass customization

Configuration design for mass customized vehicles necessitates the coordination of customer requirements, product characteristics, production processes, and logistics networks, in order to achieve rapid response to customer orders. Existing product configurators are mainly used as sales tools, and fail to account for the requirements of the entire customer order fulfillment process. In this regard, this paper proposes an Integrated Vehicle Configuration System (IVCS) to facilitate customer order processing based on information from multiple domains in a mass customization environment. An IVCS business model is proposed to incorporate the decision factors for configuration design related to different planning stages. The business model is supported by a comprehensive ontology framework, which enhances communications between different stakeholders involved in the order fulfillment process. The configuration approach is based on combinations of selective and generative rules and can be integrated with existing ERP systems. It also provides mechanisms to handle configuration rules that allow users to convert soft preferences into product specifications, bill-of-materials, and, furthermore, into logistics configurations. An example of a computerized configuration system showcases the process from customer engineering to design and production.