Search results

This paper aims to focus on production ramp up modeling on built‐to‐order (BTO) manufacturers facing customized demand. The general purpose is to present a novel approach to managing collaboration, by considering information exchange between the manufacturer and the supplier.

The methodology applies feedback control mechanism to analyze supplier responsiveness and customer order decoupling point to represent the need for collaboration. A two‐stage game is applied ahead of control system application to optimize the capacity decision, with the ultimate goal being profit maximization.

The results show that a higher product commonality degree gives more opportunity for quick response BTO supply chains, which are managed by feedback control, and at the same time to possibly mitigate the bullwhip effect caused by demand information noise.

The analytical model here focused on one product family development, so the applicability of the proposed model to the whole product portfolio should be investigated in the future.

This paper helps the manufacturer to act optimally by considering the possibility of information exchange with the supplier and deciding on the product commonality degree, in taking into account the customer's lead time requirement.

A control system model of “BTO Supply Chain” is proposed by including product commonality and response analysis in the simulation model. Furthermore, a contribution to collaborative supply chains is shown by applying a synchronized supply model to represent supplier and manufacturer communication.

The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.

Manufacturing managers as well as researchers suggest that reducing manufacturing lead time is essential for competing in world‐class manufacturing environments. To achieve world‐class manufacturing status, organizations implement a variety of programmes to decrease manufacturing lead time. Uses simulation to analyse the effect of purchased parts standardization on manufacturing lead time under the assumption of limited vendor delivery uncertainty. Creates a wide range of degrees of commonality based on three sets of multilevel product structures with the variations of end‐item demand and quantity usage. The statistical results indicate that: increased commonality lowers manufacturing lead time; a more informative commonality measure other than the well‐known degree of commonality index (DCI) is necessary to represent the actual commonality; and the distribution of purchased parts usage across different end items affects manufacturing lead time performance. The results provide important implications for both manufacturing and product design management.

To provide an overview of research published in the management accounting literature on methods for cost management in new product development, such as a target costing, life cycle costing, component commonality, and modular design.

The structured literature search covered papers about 15 different cost management methods published in 40 journals in the period 1990–2013.

The search yielded a sample of 113 different papers. Many contained information about more than one method, and this yielded 149 references to specific methods. The number of references varied strongly per cost management method and per journal. Target costing has received by far the most attention in the publications in our sample; modular design, component commonality, and life cycle costing were ranked second and joint third. Most references were published in Management Science; Management Accounting Research; and Accounting, Organizations and Society. The results were strongly influenced by Management Science and Decision Science, because cost management methods with an engineering background were published above average in these two journals (design for manufacturing, component commonality, modular design, and product platforms) while other topics were published below average in these two journals.

The scope of this review is accounting research. Future work could review the research on cost management methods in new product development published outside accounting.

The paper centers on methods for cost management, which complements reviews that focused on theoretical constructs of management accounting information and its use.

To investigate the impact of number of components (NC) and component commonality (CC) (i.e. product structure characteristics) on the effectiveness of component reservation methods and partial order releases (i.e. order review and evaluation (ORE) procedures).

Simulation experiments were conducted using a multistage production‐inventory system with MRP for planning. The results were analyzed using analysis of variance.

The results indicate that: in the presence of component availability problems, partial order release is a more effective ORE procedure than component reservation; product structure characteristics should be considered when selecting partial order release proportions; and high levels of shop congestion (SC) mitigate the influence of ORE procedures, regardless of product structure characteristics.

This study used fixed lot sizes and two factors to characterize product structures (NC and CC). Thus, studies that investigate the impact of alternative lot sizing strategies and a wider range of product structure factors could provide additional insight into the order release process.

The results provide a useful source of information for managers to consider when addressing problem orders related to material availability.

Although the literature on order review/release (ORR) recognizes the possibility of material availability problems, very little guidance is provided on how managers should react to the situation. This paper fulfils an identified information need by integrating and extending the research streams on product structure and ORE activities.

This paper aims to focus on duopolistic competition under dynamic price and production postponement for two differentiable products that share common product platform at a certain degree of product commonality.

Both price and production postponement modelling are benchmarked according to their profit in order to investigate the product substitutability effect to the profit and also their appropriateness to different competition situations. In addition, dynamic property is applied to show the demand changes effect of both strategic decisions (price and production) against demand uncertainty.

The results show that the pure price postponement is appropriate to be applied into highly customized products while pure production postponement to configurable products.

Price and production postponement decisions help managers to optimize product development as well as production strategy by considering demand and supply sides.

Price and production postponements give alternative ways to managers for deciding on how to produce products as fighting product and mass customized product.

Innovative price and production postponement models are the novelty of this paper.

To identify and examine the origins of complexity in a mass customization system and to propose an effective application sequence of variety management strategies in order to cope with this complexity.

Through the application of Suh's complexity theory an understanding of the causes of complexity in the specific context of a mass customization environment is developed. This facilitates the identification of the strategies that are adequate to tackle the problems induced by complexity.

The mass customization system is a coupled system that cannot be mastered simply. It is definitely impossible to transform it to an uncoupled system with a low complexity level. However, the effective and targeted implementation of variety management strategies at the product and process levels enables the management of this complexity by making the system more decoupled.

Complexity can be decreased if managers ensure less dependency between the satisfaction of customer requirements and position of the decoupling point. It is also advantageous to reduce the coupling level between fast delivery requirement in mass customization and the decoupling point placement. Furthermore, an effective variety management calls for the implementation of the identified strategies in an ascending order of complexity reduction potential.

The article relates the complexity theory of Suh to mass customization system, provides a framework for the classification of variety management strategies and derives managerial recommendations so as to reduce the complexity in a mass customization environment.

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process planning techniques often minimize setup times. On the contrary, grouping with respect to component geometry and frequency has been proved to further minimize assembly time. Thus, we propose the Placement Location Metric (PLM) algorithm to recognize and measure the similarity between printed circuit board (PCB) patterns. Grouping PCBs based on the geometric and frequency patterns of components in boards will form clusters of locations and, if these clusters are common between boards, similarity among layouts can be recognized. Hence, placement time will decrease if boards are grouped together with respect to the geometric similarity because the machine head will travel less. Given these notions, this study develops a new technique to group PCBs based on the essences of both component commonality and the PLM. The proposed pattern recognition method in conjunction with the Improved Group Setup (IGS) technique can be viewed as an extended enhancement to the existing Group Setup (GS) technique, which groups PCBs solely according to component similarity. Our analysis indicates that the IGS performs relatively well with respect to an array of existing setup management strategies. Experimental results also show that the IGS produces a better makespan than its counterparts over a low range of machine changeover times. These results are especially important to operations that need to manufacture quickly batches of relatively standardized products in moderate to larger volumes or in flexible cell environments. Moreover, the study provides justification to adopt different group management paradigms by electronic suppliers under a variety of processing conditions.

Assembly systems require uninterrupted components' availability to feed workstations. This paper aims to propose a methodology to help managers in evaluating and selecting the most suitable policy for materials delivery to the shop floor. The analysis focuses on three basic policies, namely kitting, just in time kanban‐based continuous supply and line storage, even including class‐based hybrid policies.

Descriptive models are developed to design components' delivery systems and to compute their performances. Empirical criteria are utilized to associate specific policies to components classes in order to implement customized hybrid line feeding policies. A case study is then included to exemplify the method application and to show its capabilities as a decision making tool.

Hybrid feeding policies may be preferable to a single feeding policy common to all components. This is shown in a representative case study. However, in general there is a priori superior method and only a comparison of alternative feeding policies based on objective performance measures can determine the best approach in specific industrial applications.

The methodology is aimed at preliminary sizing and selection of alternative line feeding systems in deterministic environments. It is not intended for detailed performance analysis of assembly systems.

Production managers are given quantitative decision tools to properly select the components' delivery method at an early decision stage. This allows trade‐offs between alternatives to be explored in order to deploy customized feeding policies differentiated on components basis to better fit specific company requirements.

The paper extends previous descriptive models for line feeding systems and includes the possibility of hybrid policies.

This paper focuses on decision making related to the use of strategic inventory allocation in product platform design. The purpose of the paper is to present a novel approach to managing product variety by considering product and manufacturing strategy, and considering the supply chain benefits.

Discrete event simulation is used for analyzing product platform performance in terms of inventory level and throughput. Simulation parameters such as lead times and safety stock allocation are optimized by using an analytical model of strategic safety stock allocation.

The results show that strategic safety stock allocation supports product platform strategy by increasing production output, and reducing inventory level and customer order queues at a higher level of product variety.

Linking the safety stock allocation and product platform strategy facilitates simultaneous product and process design by providing the most optimum platform strategy at minimum safety stock allocation.

Strategic safety stock allocation facilitates decision making with regard to lean strategy by reducing inventory level, agile strategy by increasing the amount of product variety and outputs, and responsiveness by reducing the number of customer order queues.

The paper presents an innovative customer order decoupling point decision.