Measuring the effectiveness of a mass customization and personalization strategy: a market- and organizational-capability-based index

The research of Kumar (Int J Flex Manuf Syst 16(4):287–312, 2004) is expanded to develop a methodology that measures the effectiveness of a mass customization and personalization strategy using a mass customization and personalization effectiveness index. This index extends Kumar (2004) in three significant ways: (1) it encompasses both service and manufacturing companies, (2) the assessment of product customization considers that customers assign different weights to different product features, and (3) the index captures the impact of both market perception and system capabilities. Three different measures are proposed. Which is appropriate should be a function of a particular company’s parameters. The circumstances under which each measure is best is a subject for future research. The validation and reliability of this index and these measures are also issues that should be addressed by future research.

Mass customization: manufacturing issues and taxonomic analyses

As the field of mass customization (MC) attains the status of a mature discipline, two significant research deficits stand out. First, a through metareview of the entire body of MC research that looks at the application value and rigorousness of research is overdue. Second, manufacturing issues, especially those pertaining to quality and the supply chain have been largely ignored. This issue is dedicated to both of these important areas of research. The conclusion with regards to the status of the MC field is that it is currently vibrant, with growing research volume and applications. The manufacturing issues dealt with in this issue are strategically important, dealing with quality and customization issues. The work on quality is the first of its kind: it seeks to generate a defect-tracking matrix consistent with product configurations, enabling agile identification of defects in a mass customization environment. The use of discrete event simulation to deal with the dynamically evolving customized demand so as to minimize cost and schedule disruption is innovative, timely, and profound.

Defects tracking matrix for mass customization production based on house of quality

The vision of mass customization has driven a movement toward low volume, high variety mass customization production (MCP) at low price. However, defect identification and defect tracking in such systems are extremely difficult because of the frequent reconfiguration needed by the number of different part types and the interruption of the information flow about quality with each reconfiguration of the system. It is important to quickly rebuild quality information flow with MCP system’s reconfiguration synchronously. This paper introduces a defect tracking method based on Quality Function Deployment for every MCP system module. A defects tracking matrix (DTM) based on the House of Quality directly connects manufacturing technologies with quality defects inside a MCP module. Each MCP reconfiguration requires the DTMs’ rearrangement and DTM-chain is proposed. A dynamic reconstructing algorithm synchronizes the DTM-chain with each MCP reconfiguration. A case study demonstrates the usefulness of the DTM and DTM-chain.

A dynamic heuristic-based algorithm to part input sequencing in flexible manufacturing systems for mass customization capability

In the increasingly competitive global markets, enterprises face challenges in responding to customer orders quickly, as well as producing customized products cost-effectively. This paper proposes a dynamic heuristic-based algorithm for the part input sequencing problem of flexible manufacturing systems (FMSs) in a mass customization (MC) environment. The FMS manufactures a variety of parts, and customer orders arrive dynamically with order size as small as one. Segmental set functions are established in the proposed algorithm to apply the strategy of dynamic workload balancing, and the shortest processing time (SPT) scheduling rule. Theoretical analysis is performed and the effectiveness of the algorithm in dynamic workload balancing under the complex and dynamic environment is proven. The application of the algorithm is illustrated by an example. The potential of its practical applications to the FMSs in make-to-order (MTO) supply chains is also discussed. Further research is provided.

Aligning demand and supply flexibility in custom product co-design

Flexibility of supply and demand is essential for successful implementation of a mass customization strategy that delivers sustained competitive advantage. Supply flexibility, i.e., a choice of alternative products designed to perform the same basic function, is made possible by the range of capabilities available in flexible and agile manufacturing systems and in supply chains. Demand flexibility is derived from the degree to which a customer is willing to compromise on product features or performance levels in order to meet budgetary (reflected in price) or schedule (reflected in delivery) constraints. Flexibility of both supply and demand can have significant strategic and financial value if they are properly aligned. However, customers are mostly unaware of mapping of demand flexibility on to supply flexibility and its impact on production cost and time. Recent advances in information technology have made it possible to co-design a product that involves customer on one end and the manufacturer on the other. This creates an aura and an opportunity where a middle ground between the supply and demand flexibility can be explored and a “deal” can be struck where both parties settle for a product that is beneficial to both through a negotiated settlement. In this paper, we develop a framework for such negotiations. The customer requirements are treated as a range of negotiable options instead of a set of fixed inputs. Demand and supply for customization is then matched by aligning the flexibility of manufacturing systems with customers’ requirement options. Based on this framework, a negotiation scheme is developed to assist customers and manufacturers in exploring and utilizing demand and supply flexibility information in co-design. The negotiation scheme is formulated using goal programming. Finally, an interactive problem-solving procedure is developed and implemented with an illustrative example.

A network approach for modeling and design of agile supply chains using a flexibility construct

Agility can be viewed as a need to encourage the enterprise-wide integration of flexible and core competent resources so as to offer value-added product and services in a volatile competitive environment. Since flexibility is considered a property that provides change capabilities of different enterprise-wide resources and processes in time and cost dimensions, supply chain flexibility can be considered a composite state to enterprise-wide resources to meet agility needs. Enterprise modeling frameworks depicting these composite flexibility states are difficult to model because of the complex and tacit interrelationship among system parameters and also because agility thrives on many business objectives. In view of this, the modeling framework presented in this paper is based on analytical network process (ANP) since this methodology can accommodate the complex and tacit interrelationship among factors affecting enterprise agility. The modeling framework forms a three-level network with the goal of attaining agility from the perspective of market, product, and customer as the actors. The goal depends on substrategies that address the characteristics of the three actors. Each of these substrategies further depends on manufacturing, logistic, sourcing, and information technology (IT) flexibility elements of the enterprise supply chain (SC). The research highlights that, under different environmental conditions, enterprises require synergy among appropriate supply chain flexibilities for practising agility. In the present research, the ANP modeling software tool Super Decisions™ has been used for relative prioritization of the supply chain flexibilities. We demonstrate through sensitivity analysis that dynamic conditions do require adjustments in the enterprise-wide flexibility spectrum.

Assessing capacity scalability policies in RMS using system dynamics

This paper presents a model for assessing different capacity scalability policies in Reconfigurable Manufacturing System (RMS) for different changing demand scenarios. The novelty of this approach is two fold: (1) it is the first attempt to explore different capacity scalability policies in RMS based on multiple performance measures, mainly scaling rate, Work In Process level, inventory level and backlog level; and (2) the dynamic scalability process in RMS is modeled for the first time using System Dynamics. Different policies for capacity scalability for various demand scenarios were assessed. Numerical simulation results obtained using the developed capacity scalability model showed that the best capacity scalability policy to be adopted for RMS is dependent on the anticipated demand pattern as well as the various manufacturing objectives. The presented assessment results will help the capacity scalability planners better decide the different tradeoffs between the competing strategic and operational objectives of the manufacturing enterprise, before setting the suitable capacity scalability plan parameters.

Mass customization of travel packages: data mining approach

This article employs a mass customization strategy to design travel packages that minimize the operation and processing costs for the service provider on one hand, while aligning the components of the packages to maximize customer satisfaction on the other. Data mining is used to identify rules of association to develop this model. Hidden relations in the massive travel agencies’ databases are revealed by using the association rules technique to customize travel packages according to customers’ requirements. This approach leads to fewer, but more manageable and popular travel package promotions. The overall package selection problem is modeled as an integer program that minimizes costs of operation and processing. Two different solution approaches were used: a mathematical modeling language approach and a heuristic algorithm approach. An illustrative numerical example based on a synthetic data set is also presented.

Modeling customized product configuration in large assembly manufacturing with supply-chain considerations

Dynamic variability in low-volume and highly customized products of a large assembly manufacturing system with an integrated supply chain has been very challenging to capture. Design and product configurations most likely impact outcomes of such broad variability. This article presents a framework to encompass this completely integrated system for using discrete event simulation as a modeling method. The system modeling framework addresses factors including customized configuration attributes and individual customer-preferred considerations for customized configurations. The framework is intended to aid decision-making concerning cost and schedule impacts associated with customization options chosen throughout the supply chain. A real-world example drawn from aerospace is included to demonstrate and validate the operational capability of the proposed framework.

Economic and strategic perspectives on investing in RMS and FMS

The evolution of manufacturing systems, according to changing internal and external conditions, requires design and assessment techniques that consider both strategic and financial criteria to evaluate the suitability of the Flexible and Reconfigurable system solutions in addressing these variations. In this paper, a fuzzy multi-objective mixed integer optimization model to evaluate RMS investments used in a multiple product demand environment is presented. The model incorporates in-house production and outsourcing options, machine acquisition and disposal costs, operational costs, and re-configuration cost and duration for the utilized modular machines. The resulting system configurations are optimized for lifecycle costs, responsiveness performance, and system structural complexity simultaneously. A complexity metric that incorporates the quantity of information using an entropy approach is used to represent the inherent structural complexity of the considered system configurations. It accounts for the complexity of the machine modules in a manufacturing system through the use of an index derived from a newly developed manufacturing systems classification code, which captures the effect machine types and technologies on the system’s structural complexity. A metric is proposed to measure the responsiveness ability and efficiency as well as the overall capability of each machine and effectiveness of machines changeover. The application of the developed planning and assessment model that incorporates these three criteria is illustrated with a case study where FMS and RMS alternatives were compared. The suitable conditions for investing in RMS are also discussed.

Influence of weave of carbon fabric on abrasive wear performance of polyetherimide composites

Three composites of Polyetherimide (PEI) reinforced with carbon fabric (CF) of three weaves viz. plain, twill and satin-4 H were developed keeping the amount of fabric constant (55% by vol.). Studies on mechanical properties confirmed that the twill weave composite (T) showed the highest strength, modulus (both tensile and flexural) and interlaminar shear strength (ILSS) followed by satin (S) and plain weave (P) composites. The performance order, however, was reverse in the case of toughness and elongation to break. Specific wear rate in a single-pass, unidirectional and un-lubricated abrasive wear mode against SiC paper showed strong influence of weave in mild wear condition (load 10 N). Composite S showed the highest wear resistance (W _R) followed by composites T and P. With increase in load, the difference in performance diminished to the extent that at 40 N, it was almost similar for all the three composites. This was correlated with the difference in the length of the fibers between crossover points which, in turn, allowed the microdisplacement of fibers in the composites during abrasion. This was supported by the SEM.

Interpretation of experiments on ZDDP anti-wear films through pressure-induced cross-linking

We review a recently developed molecular-level theory for the formation and functionality of zinc dialkyldithiophosphate anti-wear films [N. J. Mosey, M. H. Müser and T. K. Woo, Science 307 (2005) 1612]. This theory is based on the idea that pressure-induced cross-linking leads to chemically connected networks. The formation of cross-links modifies the mechanical properties of the films such that wear inhibition may be enhanced. Furthermore, the networks remain intact upon release of the pressure, which resists flow of the film out of the contact area. The ability of the theory to account for a diverse body of experimental data related to anti-wear additives and films is discussed. Routes towards the development of new AW additives are also suggested on the basis of the theory.

Optimal configuration selection for Reconfigurable Manufacturing Systems

The selection of Reconfigurable Manufacturing Systems (RMS) configurations that include arrangement of machines, equipment selection, and assignment of operations, has a significant impact on their performance. This paper reviews the relevant literature and highlights the gaps that exist in this area of research. A novel “RMS Configuration Selection Approach” is introduced. It consists of two phases; the first deals with the selection of the near-optimal alternative configurations for each possible demand scenario over the considered configuration periods. It uses a constraint satisfaction procedure and powerful meta-heuristics, real-coded Genetic Algorithms (GAs) and Tabu Search (TS), for the continuous optimization of capital cost and system availability. The second phase utilizes integer-coded GAs and TS to determine the alternatives, from those produced in the first phase, that would optimize the degree of transition smoothness over the planning horizon. It uses a stochastic model of the level of reconfiguration smoothness (RS) across all the configuration periods in the planning horizon according to the anticipated demand scenarios. This model is based on a RS metric and a reconfiguration planning procedure that guide the development of execution plans for reconfiguration. The developed approach is demonstrated and validated using a case study. It was shown that it is possible to provide the manufacturing capacity and functionality needed when needed while minimizing the reconfiguration effort. The proposed approach can provide decision support for management in selecting RMS configurations at the beginning of each configuration period.

Impact of ramp-up on the optimal capacity-related reconfiguration policy

This paper presents an optimal solution, based on Markov decision theory, for the problem of optimal capacity-related reconfiguration of manufacturing systems, under stochastic market demand. Both capacity expansion and reduction are considered. The solution quantitatively takes into account the effect of the ramp-up phenomenon, following each reconfiguration, on the optimal policy. A closed-form solution is presented for when product demand is independently and generally distributed over time. A real case concerning a flexible manufacturing line in the automotive sector is shown, to prove that ignoring the ramp-up effect in the decision process can lead to significant increases in overall costs.

Optimum concentration of reinforcement and solid lubricant in polyamide 12 composites for best tribo-performance in two wear modes

In general polymers are used in the form of composites (fiber reinforced, solid lubricated or both) in tribo-applications, where they may encounter more than one type of wear situations or mechanisms to different extents. The area of investigating the optimum concentration of fillers for best combination of tribo-performance in different wear modes and mechanical strength is sparingly researched. In this paper, research findings on the influence of the contents of short carbon fibers (CF) and PTFE (particulate form) in Polyamide (PA) 12 on friction and wear behavior in two wear modes (adhesive and fretting) have been reported. With increase in contents of CF up to 30% (vol) most of the mechanical properties and tribo-performance improved in adhesive and fretting wear modes. With a view to enhance it further, PTFE was added step by step in the best performing composite (PA+30% CF). This boosted the tribo-performance further, however, at the cost of strength properties. With increase in PTFE percentage (10, 15 and 20% by vol), specific wear rate (K _o) and friction coefficient (μ) both decreased appreciably in adhesive as well as fretting wear modes. The composite consisting of 30% CF and 20% PTFE showed lowest values for μ and K _o rendering it the best tribo-combination for all practical purposes. The abrasive wear behavior of composites was also investigated. However, wear performance in this mode showed exactly opposite trends. Inclusion of fibers or combination of fibers and PTFE proved detrimental.

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Agent-based supply-chain planning in the forest products industry

The new economic challenges and recent trends in globalization have made it very difficult for Canadian forest product companies to improve their financial position without the coordinated involvement of the entire company, including their supply chains (distributed facilities, company offices, industrial customers, and distributors). Such a new level of efficiency involves their distributed facilities and offices spread around the world, and their customers. One consequence of this new reality is that forest products companies are now facing the need to re-engineer their organizational processes and business practices with their partners. To do this they must adopt new technologies to support the coordination of their planning and control efforts in a customer-centered environment. This paper first proposes a generic software architecture for development of an experimentation environment to design and test distributed advanced planning and scheduling systems. This architecture enables combination of agent-based technology and operations research-based tools in order to first take advantage of the ability of agent technology to integrate distributed decision problems, and, second, to take advantage of the ability of operations research to develop and exploit specific normative decision models. Next, this paper describes how this architecture has been configured into an advanced planning and scheduling tool for the lumber industry. Finally, we present how an application of this advanced planning tool is currently being validated and tested in a real manufacturing setting.

The impact of operations redesign on the safety stock investment in supply chains

This study is motivated by a real problem encountered in the manufacturing and distribution process at a local electronic manufacturer of security devices. We investigate the impact of operations redesign (i.e., operations merging) on the cost of safety stock in a supply chain. A simple safety stock method is used to derive a model for estimating safety stock levels. Our result shows that operations redesign can have a significant impact on safety stock investment. We extend and complement the existing literature in the following aspects: (i) we address the issue of safety stock deployment, i.e., we not only investigate the problem of how many operations should be delayed, but also determine which operations need to be delayed, (ii) we provide an efficient heuristic algorithm to determine which operations need to be merged, and (iii) we find the optimal operations redesign strategies under some special cases. Our analysis also reveals some important conditions and insights for better operations redesign, which enable us not only to decide when an operations redesign is appropriate, but also to suggest the scale and the format of the operations redesign.

Observations on the present and future of mass customization

A demanding task for many companies today is that of learning to regard customers as individuals, of proactively developing products and services according to the individual customer preferences, and of subsequently producing and distributing these offerings. Over the last decade, mass customization has emerged as an effective approach for tackling precisely this task. In this paper, I discuss the background of mass customization and the elements of this strategy. I will then comment on the implementation of mass customization in practice. I will end with a brief discussion of alternative strategies in this domain, namely personalization and matching services.     

Adequate and economic factory transformability and the effects on logistical performance

Objective-oriented factory planning is a prerequisite for the economic operation of a factory. As intensive discussions in the literature as well as practical findings in factories over the years show, transformability and logistics are among the key objectives of a factory. It is striking, however, that both objectives have not so far been related to each other. Based on these findings, a method for evaluating the actual as well as the target transformability of a factory has been developed. It allows the user to assess whether the factory possesses adequate and economic transformability. In order to make the method more manageable for users in practice, a software tool is presented, and a benchmarking has been derived from the data collected by evaluating factory transformability. In addition, it has been found that transformability can influence logistics. A procedure will be presented that allows major means of adjustment to be found that improve the logistics objectives of a factory by using transformability. Finally, the outlook for future developments is discussed.

A modeling approach for evaluating capacity flexibilities in uncertain markets

The flexibility of production capacities is a means for coping with the challenges in today’s market environment, especially when dealing with strong fluctuations in customers’ demands. The reliable planning and evaluation of these capacities and their inherent flexibilities are considered an important task for many companies. This paper presents a capacity/cost model that considers the impact of market uncertainties and the corresponding capacity flexibilities. It proposes a demand forecasting method, a modeling approach for capacity-related flexibilities and the analysis of the economical correlation between available and required capacities. Based on this, capacity planning can be optimized using this model. The different steps of applying this modeling approach are illustrated with the aid of an example.