Delayed Product Differentiation Research Articles

CAPP-GPT: A computer-aided process planning-generative pretrained transformer framework for smart manufacturing

Smart manufacturing (SM) constitutes the backbone of Industry 4.0 (I4.0), allowing for heightened autonomy of the various interacting cyber-physical systems, making the various entities on the production floor. Connectivity, a vital enabler, plays a crucial role through state-of-the-art Digital Twinning (DT) technologies driven by underlying innovations like the industrial Internet of Things, Cloud Computing, and advancements in sensory devices. DT, which plays a vital role in the various planning functions under the production and operations management umbrella, is being used in the developed combined CAPP-GPT (Computer-Aided Process Planning-Generative Pretrained Transformer) and production scheduling approach to address disruptions on the shopfloor and in self-healing of the manufacturing processes at a micro-CAPP level by optimally adapting the process parameters and the developed toolpath on the fly based on online process signature measurements. In a leap commensurate with that which has taken place in Natural Language Processing-Large Language Models (Chat-GPT), similar efforts are currently being undertaken to parse CAD data structures and blueprints, fusing operations research and predictive analytics algorithms to carry out setup planning as well as sequencing and grouping manufacturing sub-operations. A hybridized Optimization and Machine Learning (ML) approach is employed where Logical Analysis of Data is used to solve the problem heuristically, exploiting various generative and variant methods at heart. Another extension of this macro-CAPP problem is being tackled by integrating the problem with delayed product differentiation, lot-sizing, and transfer line balance for futuristic batch-production shops employing Hybrid Manufacturing (HM) and Smart Assembly. At the micro-CAPP level, HM process parameters are optimized using a comprehensive approach employing the Taguchi loss function to assess surface roughness, internal failure costs, and other criteria, including greenhouse gas emissions and expended energy. Online measurements of the process signatures are also employed to adapt the initial set of process parameters using different automatic control schemes. ML is used to identify the process parameters carrying simulations on Simulink before the system is deployed.

A Sustainable Product Multi-Platform Planning Model for Assembly and Disassembly Process

Abstract The development of a product platform is an effective strategy to respond to dynamic market demands, decrease lead time, and delay product differentiation. However, the traditional product platform configuration method cannot satisfy the sustainability requirements for modern products. To solve this problem, a sustainable product multi-platform (SPMP) model for assembly/disassembly technology is proposed in this article. The proposed SPMP model measures the energy consumption of module instances during the installation based on the platform-based assembly index (PAI) and platform-based disassembly index (PDI), and provides a multi-platform solution for the assembly of the product family. To demonstrate the effectiveness of the proposed method, two product family cases are discussed. A simplified case shows that multi-objective particle swarm optimization (MOPSO) algorithm has a stronger optimization ability than the linear programing method in reducing the product processing cost. The hair dryer family case demonstrates that the proposed method reduces the energy consumption during assembly by linking sustainability to the product design.

A two-step methodology for product platform design and assessment in high-variety manufacturing

The delayed product differentiation (DPD) recently rose as a hybrid production strategy able to overcome the main limits of make to stock (MTS) and make to order (MTO), guaranteeing the management of high variety and keeping low storage cost and quick response time by using the so-called product platforms. These platforms are a set of sub-systems forming a common structure from which a set of derivative variants can be efficiently produced. Platforms are manufactured and stocked following an MTS strategy. Then, they are customized into different variants, following an MTO strategy. Current literature proposes methods for platform design mainly using optimization techniques, which usually have a high computational complexity for efficiently managing real-size industrial instances in the modern mass customization era. Hence, efficient algorithms need to be developed to manage the product platforms design for such instances. To fill this gap, this paper proposes a two-step methodology for product platforms design and assessment in high-variety manufacturing. The design step involves the use of a novel modified algorithm for solving the longest common subsequence (LCS) problem and of the k-medoids clustering for the identification of the platform structure and the assignment of the variants to the platforms. The platforms are then assessed against a set of industrial and market metrics, i.e. the MTS cost, the variety, the customer responsiveness, and the variants production cost. The evaluation of the platform set against such a combined set of drivers enhancing both company and market perspectives is missing in the literature. A real case study dealing with the manufacturing of a family of valves exemplifies the efficiency of the methodology in supporting companies in managing high-variety to best balance the proposed metrics.

МІЖНАРОДНИЙ ТРАНСПОРТНО-ЛОІГСТИЧНИЙ БІЗНЕС В СИСТЕМІ МІЖНАРОДНОЇ ЕКОНОМІЧНОЇ БЕЗПЕКИ

The article analyzes the current trends of the international transport and logistics business in the system of international economic security. The development of the integration of the world economy and the globalization of business contribute to the creation of international logistics systems and global supply chains. The article highlights the main directions of increasing the efficiency of supply chain management and indicates the sources of increasing the efficiency of this process. The key negative aspects that prevent the effective functioning of international transport and logistics systems have been identified. A comparison is made between the traditional approach to production and the logistic approach, when the manufacturer starts production only when a specific order is received. The inventory management system of the seller is characterized. An overview of modern trends in the international transport and logistics business was carried out, in particular: increasing turnover while shortening delivery times, increasing investments in logistics startups by venture funds, customization, the use of multimodal transport and logistics centers, ecological logistics, etc. The main directions in which digital logistics centers can help logistics companies to achieve success are determined, in particular, it was determined that success will be achieved through the use of the method of «postponement» or «delayed product differentiation», the organization of e-commerce logistics, containerization, increasing the share of direct express deliveries from the producer to the consumer, bypassing intermediaries and intermediate warehouses, electronic exchange of data and various information, the growth of the agricultural machinery market, the use of multimodal transport and logistics centers, as well as clear planning of supply chains, flexibility, management of stocks and volumes. Also, a hypothesis was put forward about the emergence of a new term «logtech company», which includes not only the creation of new technologies, but also new logistics business models based on the joint use (shared use) of transportation.

Bio-inspired phylogenetics for designing product platforms and delayed differentiation utilizing hybrid additive/subtractive manufacturing

"Biologicalisation in Manufacturing" is used to integrate biological and bio-inspired processes, principles and resources into manufacturing to handle challenges such as product proliferation. This paper introduces a product variety management methodology utilizing bio-inspired phylogenetics for designing product platforms for the delayed product differentiation using hybrid additive/subtractive manufacturing technologies. The median joining phylogenetic network, an ancestral sequence recognition method used in biology, is applied. This method is used to design product platforms that resemble the common ancestors in nature and determine the process plans for the platform customization that resembles the adaption in nature. A new feature extraction procedure is introduced to extract the additive and subtractive features of a product family. Two case studies, guiding bushings and flanges product families, are used for demonstration. The developed methodology improves the responsiveness and product mix flexibility and decreases the storage costs.

A multi-item batch fabrication problem featuring delayed product differentiation, outsourcing, and quality assurance

Variety, quality, and rapid response are becoming a trend in customer requirements in the contemporary competitive markets. Thus, an increasing number of manufacturers are frequently seeking alternatives such as redesigning their fabrication scheme and outsourcing strategy to meet the client’s expectations effectively with minimum operating costs and limited in-house capacity. Inspired by the potential benefits of delay differentiation, outsourcing, and quality assurance policies in the multi-item production planning, this study explores a single-machine two-stage multi-item batch fabrication problem considering the abovementioned features. Stage one is the fabrication of all the required common parts, and stage two is manufacturing the end products. A predetermined portion of common parts is supplied by an external contractor to reduce the uptime of stage one. Both stages have imperfect in-house production processes. The defective items produced are identified, and they are either reworked or removed to ensure the quality of the finished batch. We develop a model to depict the problem explicitly. Modeling, formulation, derivation, and optimization methods assist us in deriving a cost-minimized cycle time solution. Moreover, the proposed model can analyze and expose the diverse features of the problem to help managerial decision-making. An example of this is the individual/ collective influence of postponement, outsourcing, and quality reassurance policies on the optimal cycle time solution, utilization, uptime of each stage, total system cost, and individual cost contributors.

A two-stage multiproduct EMQ-based model with delayed differentiation and overtime option for common part’s fabrication

This study explores the two-stage multiproduct economic manufacturing quantity (EMQ)-based system with delayed product differentiation and overtime option for fabrication of common parts. The classic EMQ model determines optimal lot size under assumptions of steady production rate; however, managers of present-day’s manufacturing firms, operating in a highly competitive global business environment, must constantly seeks ways to strengthen their competitive forces, such strategies include: (i) to increase machine utilization through planning multiproduct fabrication; (ii) to evaluate different production schemes to reduce cost, e.g., a delayed differentiation strategy, when a common intermediate product exists in a multiproduct system, wherein all required common parts are manufactured in stage one and final multi-product are produced in the second stage; and (iii) to reduce the cycle time through implementing an overtime strategy. This study is motivated and intended to address the aforementioned real factors. We use mathematical modeling to depict the problem first, then employ the optimization technique to solve it. Our objectives are to not only decide the optimal replenishing policy, but also to explore the effect and joint influence of the postponement and overtime strategy on the optimal policy, machine utilization, system costs, and relevant cost components in the system. Without this in-depth investigation, various crucial information relating to decision making will still be inaccessible to managers in this field.

Open manufacturing: a design-for-resilience approach

Open systems have been of interest to the research and industrial community for decades, e.g. software development, telecommunication, and innovation. The presence of open manufacturing enterprises in a cloud calls for broadly interpretable models. Though there is no global standard for representation of digital models of processes and systems in a cloud, the existing process modelling methodologies and languages are of interest to the manufacturing cloud. The models residing in the cloud need to be configured and reconfigured to meet different objectives, including complexity reduction and interpretability which coincide with the resilience requirements. Digitisation, greater openness, and growing service orientation of manufacturing offer opportunities to address resilience at the design rather than the operations stage. An algorithm is presented for complexity reduction of digital models. The complexity reduction algorithm decomposes complex structures and enhances interpretability and visibility of their components. The same algorithm and its variants could serve other known concepts supporting resilience such as modularity of products and processes as well as delayed product differentiation. The ideas introduced in the paper and the complexity reduction algorithm of digital models are illustrated with examples. Properties of the graph and matrix representations produced by the algorithm are discussed.

Combining the delayed differentiation policy and common parts' partial outsourcing strategy into a multi-item FPR-based system

This study investigates a multi-item finite production rate(FPR-) based system incorporating a delayed product differentiation policy and common parts' outsourcing strategy. A two-stage fabrication scheme is proposed, wherein, in stage one, all common parts of the end products (assuming they have a known completion rate as compared with the finished products) are partially produced in-house and partially supplied by an outside contractor with an extra unit outsourcing; in stage two, all end products are finished in sequence, under a rotation fabrication cycle time discipline. An explicit model is developed to clearly represent the proposed problem. Through the optimization technique, the optimal rotation cycle decision is obtained. Thus, diverse characteristics of this particular multi-item, FPR-based system with postponement and outsourcing strategies can now be revealed. As demonstrated by numerical illustrations, these characteristics include the (i) convexity of the system cost function, (ii) impact of common parts' outsourcing strategy on the utilization, (iii) breakup of system cost components, (iv) combined impact of the outsourcing ratio and common parts' completion rate on the system cost function, and (v) effect of the outsourcing ratio on optimal rotation cycle decision. Our decision-support-type system can facilitate production managers in achieving their goals of reducing orders' response times and minimizing the overall system cost.

A delayed product differentiation model for cloud manufacturing

Abstract Cloud manufacturing (CMfg) enables in-depth customization but raises demand uncertainties. Delayed product differentiation (DPD) is one attempt to solve such problem. However, current DPD approaches are mostly focused on the production of a dominant company, which tend to hold the supply chains with fixed network structures. Nevertheless, CMfg requires more flexible structures (agile supply chain) to facilitate multiple manufacturers to access external resources with various manners. Therefore, linking DPD to CMfg becomes an important research topic, and the paper proposes an optimization model, namely DPDCM, for such purpose. The model is established on the basis of integrating the order-release, generic inventory and sourcing decisions, and is formulated as an integer programming problem, to meet diverse requirements of companies for carrying out DPD in CMfg environment. Case studies on bicycle and industrial-transformer manufacturing have been applied and analyzed, in which genetic algorithm is adopted to obtain near-optimal solutions. It validates the effectiveness, flexibility and universality of DPDCM.

Apparel Mass Customization Technology Based on Postponement Manufacturing

Apparel mass customization can effectively meet consumers personalized, diversified needs and reasonably control production costs and delivery time, and the postponement manufacturing is one of its core strategies. Typical cases that garment industry applied postponed strategy into the production are introduced systematically, and present two key technologies-product differentiation delay and design production modularization. Delay product differentiation which is driven into production process by accurate information, avoids the drawbacks of forecasting relying on the experience, and modularization achieves large scale production as well as get the goal of customization. The postponed manufacturing theory, methods, cases, and implementation strategy in the apparel industry field have been explained systematically in order to provide new ideas and references for the apparel enterprises which are in the transformation and upgrading process to obtain core competitiveness and to open up new production business model.

Modular product platform configuration and co-planning of assembly lines using assembly and disassembly

Formation of products platforms is carried out during the planning stage and very often separately from the planning of corresponding assembly lines. There is a dearth of literature which considers the different aspects of fully integrating platform design, product family formation, assembly line design, delayed product differentiation, and new concepts of mass customization. A Modular Product Platform Configuration model which uses assembly and disassembly for configuring product variants and Co-Planning of products platforms (MPCC) and their assembly Lines is presented. It is used to co-plan the common platform components and the associated product families simultaneously with the planning of its corresponding mixed-model assembly line. Using both assembly and disassembly to customize the product family platform in order to generate product variants is not commonly discussed in literature. It is defined as the formation of platforms for use to derive multiple products by including many components not shared by every product. The platform is then customized by assembling or disassembling components to form different product variants. The model is formulated using mixed integer mathematical programming to minimize the number of assembly stations and cycle time. Two case studies are used for verification and demonstration. They illustrated the ability of the MPCC model to integrate the planning of product platform, product families and the number of assembly stations required to assemble and disassemble components from mass-assembled product platforms to derive new product variants.

Poisoning of domestic animals: 2014 data from Poison Control Centre of Milan

Formation of products platforms is carried out during the planning stage and very often separately from the planning of corresponding assembly lines. There is a dearth of literature which considers the different aspects of fully integrating platform design, product family formation, assembly line design, delayed product differentiation, and new concepts of mass customization. A Modular Product Platform Configuration model which uses assembly and disassembly for configuring product variants and Co-Planning of products platforms (MPCC) and their assembly Lines is presented. It is used to co-plan the common platform components and the associated product families simultaneously with the planning of its corresponding mixed-model assembly line. Using both assembly and disassembly to customize the product family platform in order to generate product variants is not commonly discussed in literature. It is defined as the formation of platforms for use to derive multiple products by including many components not shared by every product. The platform is then customized by assembling or disassembling components to form different product variants. The model is formulated using mixed integer mathematical programming to minimize the number of assembly stations and cycle time. Two case studies are used for verification and demonstration. They illustrated the ability of the MPCC model to integrate the planning of product platform, product families and the number of assembly stations required to assemble and disassemble components from mass-assembled product platforms to derive new product variants.

Late customization strategy with service levels requirements

Both supply issues and interaction between various stages of a production network are common occurrences in product customization under a delayed differentiation strategy. This paper studies non-decouple systems for product customization in the context of a single-market segment under a delayed differentiation strategy by incorporating supply issues and interaction between various stages of a production network. We analyze two alternatives for customizing two individual products. One alternative is the contractual obligations for raw materials delivery where the supplier is responsible for maintaining certain inventory service levels agreements. The other alternative is the customer demand requirements where the manufacturer is responsible for maintaining certain end-products service levels to prevent customer erosion. We characterize the service level requirements in both scenarios and determine the optimal customization point of the production network where the practitioner can operate at minimum cost. We use a Bayesian Belief Networks method to model interaction between stages of the production network and derive the inventory service level requirements. A mini-case involving the customization of a personal desktop computer is used to illustrate the applicability of this framework. We also compare the benefits of delayed product differentiation under non-decouple systems and the traditional decouple systems and provide insights into how firms can choose the right strategy to effectively compete.

Discussion of “Method to Implement Delayed Product Differentiation in Construction of High-Rise Apartment Building Projects” by Cecília Gravina da Rocha and Sergio Luiz Kemmer

Ibrahim Bakry, Ph.D., S.M.ASCE; Osama Moselhi, F.ASCE; and Tarek Zayed, M.ASCE Postdoctoral Fellow, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., 1455 Blvd. de Maisonneuve W, Montreal, QC, Canada H3G 1M8 (corresponding author). E-mail: bakryibrahim@yahoo.com Professor, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., 1455 Blvd. de Maisonneuve W, Montreal, QC, Canada H3G 1M8. E-mail: moselhi@encs.concordia.ca Professor, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., 1455 Blvd. de Maisonneuve W, Montreal, QC, Canada H3G 1M8. E-mail: Tarek.Zayed@concordia.ca

Closure to “Method to Implement Delayed Product Differentiation in Construction of High-Rise Apartment Building Projects” by Cecília Gravina da Rocha and Sergio Luiz Kemmer

Ibrahim Bakry, Ph.D., S.M.ASCE; Osama Moselhi, F.ASCE; and Tarek Zayed, M.ASCE Postdoctoral Fellow, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., 1455 Blvd. de Maisonneuve W, Montreal, QC, Canada H3G 1M8 (corresponding author). E-mail: bakryibrahim@yahoo.com Professor, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., 1455 Blvd. de Maisonneuve W, Montreal, QC, Canada H3G 1M8. E-mail: moselhi@encs.concordia.ca Professor, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., 1455 Blvd. de Maisonneuve W, Montreal, QC, Canada H3G 1M8. E-mail: Tarek.Zayed@concordia.ca

A delayed product customization cost model with supplier delivery performance

Abstract The concept of delayed product differentiation has received considerable attention in the research literature in recent years. However, few analytical models explain and quantify the benefits of delayed product differentiation strategy with additional consideration of supplier delivery performance. This paper proposes a delayed product differentiation model in which a supply of raw materials is integrated at the beginning of the production process to match uncertain demand in a cost-effective way given the constraint of lead time delivery window. It develops insights regarding a delayed product differentiation strategy and shows that with respect to delivery windows, supplier delivery performance plays an important role in the determination of the optimal point of differentiation. This study also shows that when the “ on-time ” and the “ late ” portions of the delivery window are constant, the proposed cost function coincides with similar models found in the literature. An extension of this work also reveals that when the customer service level varies across various production stages, its choice affects the decision to delay or postpone the customization point. A mini industrial case involving the customization of a personal desktop computer is used to illustrate the applicability of the resulting framework.

Developing assembly line layout for delayed product differentiation using phylogenetic networks

Effective formation of product platforms helps adapt to product demand changes and decrease time-to-market and lead time. The product platform groups the core elements of product family members into a common module used to derive different product variants by combining it with different components. A new delayed product differentiation (DPD) platform network model, which applies median-joining phylogenetic networks (MJPN), is proposed. It is used for forming product platforms and determining the assembly line layout of modular product families. The MJPN is traditionally used for DNA sequences’ mapping, analysis, clustering and tracing evolutionary trends. The concept of assembly/disassembly modular platforms, whereby both assembly and disassembly of components are used to derive the final product variants from the platform, is utilised. The proposed model determines the required number and composition of a product platform and defines the DPD points. The developed dynamic assembly/disassembly platforms enhance routing and product mix flexibility due to having different platforms that can be used to produce the same product variant. A family of household kettles is used to demonstrate the application of the proposed model. A metric is presented for determining the effectiveness of a given platform in delaying the product differentiation, hence increasing the efficiency of mass customisation. The proposed metric, applied to the case study, demonstrated that the proposed platform formation model using MJPN is more capable of postponing the product differentiation point.

Method to Implement Delayed Product Differentiation in Construction of High-Rise Apartment Building Projects

AbstractThe customization of apartments can add value and increase clients’ satisfaction. However, companies offering such a strategy often face problems in managing the construction process. Delayed product differentiation—postponing the tasks that customize a product as much as possible—is a principle applied in manufacturing that enables companies to better cope with customization. Yet, it has not been widely explored in the building industry. This paper proposes a method to implement this principle in the construction of high-rise apartment building projects using the line-of-balance technique. First, the method is described, followed by its application in a project developed by a construction company. A comparison between the long-term plan devised using the proposed method and the initial plan shows a postponement of the decoupling point (namely, the first task that customizes an apartment) of approximately 42 weeks. At the end, the potential benefits and difficulties in creating such postponement a...

Evaluation of manufacturing system redesign with multiple points of product differentiation

This paper presents a cost model for evaluating the redesign of manufacturing systems with delayed product differentiation (i.e. postponement). In addition to considering multiple points of product differentiation, the proposed model explicitly includes the operational delay cost of intermediate (semi-finished or generic) products waiting at points of postponement because of inefficient scheduling or insufficient capacity, as well as the penalty cost of late-delivered and cancelled orders owing to stockout. This operational delay cost may be particularly prominent in continuous production systems with delayed product differentiation, and is critical in analysing the trade-off between the waiting delay of end products in push-based systems and the operational delay of intermediate products in push–pull systems. This cost model was adopted to analyse the cost and benefit of the postponement strategy implemented by a large copper strips manufacturer in Taiwan. In this case, both manufacturing and logistics postponements were adopted in the redesigned manufacturing system, which involved a third-party logistics service provider. The results demonstrate that the benefits of implementing postponement are largely owing to the reduction in inventory related costs. In addition, we found that both penalty cost and operational delay cost account for a significant portion of the total cost saving resulting from implementing the postponement strategy, whereas no previous models have included these two cost items.