Increasing accuracy and robustness of order promises

Accurate order promising is a key requirement for customer satisfaction. Nevertheless, practitioners struggle with the reliability of the delivery dates they promise to customers. Consequently, the costs of demand fulfilment soar due to intensified communication, emergency processes in logistics and acquisition of costly external production resources. We identify and formalise product and process flexibilities in supply chains that can be exploited in production planning. Product flexibility is the possibility to produce several kinds of products from one predecessor product. Process flexibility is the possibility to use one production process to manufacture several products. In order to increase the accuracy and robustness of delivery dates, we develop an order promising methodology able to deal with demand mix uncertainty and heterogeneous customer order lead times. The approach anticipates changes in production plans made possible by product and process flexibilities. In a numerical study based on a case from the semiconductor industry, we demonstrate that our method increases the accuracy and robustness of order promises. For the studied case, we find that the consideration of process flexibility is more important for the generation of accurate and robust order promises than the consideration of product flexibility.     

An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain

This paper presents a new weighted fuzzy multi-objective model to integrated supplier selection, order quantity allocation and customer order scheduling problem to prepare a responsive and order-oriented supply chain in a make-to-order manufacturing system. Total cost and quality of purchased parts as well as the reliability of on-time delivery of customer orders are regarded as the objectives of the model. On the other hand, flexible suppliers can contribute to the responsiveness and flexibility of entire supply chain in the face of uncertain customer orders. Therefore, a mathematical measure is developed for evaluating the volume flexibility of suppliers and is considered as the other objective of the model. Furthermore, by considering the effect of interdependencies between the selection criteria and to handle inconsistent and uncertain judgments, a fuzzy analytic network process method is used to identify top suppliers and consider as the last objective. In order to optimise these objectives, the decision-maker needs to decide from which supplier to purchase parts needed to assemble the customer orders, how to allocate the demand for parts between the selected suppliers, and how to schedule the customer orders for assembled products over the planning time horizon. Numerical examples are presented and computational analysis is reported.     

Supply chain flexibility and operations optimisation under demand uncertainty: a case in disaster relief

After a disaster happens, emergency response operations are critical to save humans’ lives and properties. The limited resources and time requirements call for coordinated supply chain operations. This paper studies supply chain operations for rescue kits in disaster reliefs, motivated by a real-world application. The objective is to minimise the total tardiness and peak tardiness of product delivery over the multi-period planning horizon. One major challenge is the lack of reliable prediction of customer demand in disasters. In order to cope with demand uncertainty while maintaining the tractability of the optimisation model, we decompose the demand into two components: a relatively stable base demand predicted by historical data and unpredictable demand surges. For the base demand, an optimisation model is developed to optimise the production and distribution operations, as well as the inventory replenishment policy for manufacturers and distribution centres, so as to minimise the total tardiness. For the demand surges, we propose to deploy supply chain flexibility to cope with the uncertainty. An empirical study shows the effectiveness of increasing supply chain flexibility and suggests some managerial insights on configuring such flexibility in emergency operations.     

Flexible supply network planning for hybrid shipment: a case study of memory module industry

The modern supply chain network has geographically spread out across the globe. The performance of a customer service level is highly dependent on the effectiveness of its supply chain planning. To improve the service provided to downstream customers, planners must not only decide order allocation among multiple distribution centres but also consider reducing the order-to-delivery time. Directed shipment delivery from manufacturing sites provides the flexibility of direct shipment; however, it also makes order allocation more difficult. In this study, a flexible supply network planning (FSNP) model based on integer linear programming is developed for the memory module industry. In addition to multisite order allocation planning, the FSNP model explicitly considers directed shipment from manufacturing sites for reducing the order-to-delivery time. Furthermore, the combination of characteristics of the memory module industry, such as multilevel and multisite production environments, multiple-to-multiple product structures, transportation and production lead times and capacity constraints, makes FSNP highly complicated. The results of the experiments reveal that the FSNP model improves supply chain planning regarding order due date and inventory and transportation costs.     

Development and application of a worker assignment model to evaluate a lean manufacturing cell

In lean manufacturing environments, cross-training is often used to achieve multi-skilling in order to increase flexibility in meeting fluctuating demand, to create a shared sense of responsibility, and to balance workload between cross-trained workers. This paper presents a model that assigns workers to tasks within a lean manufacturing cell while minimizing net present cost. In determining how to assign workers to tasks, the model addresses production requirements to meet customer demand, skill depth requirements for tasks, varying quality levels based on skill depth, and job rotation to retain skills for a cross-trained workforce. The model generates an assignment of workers to tasks and determines the training necessary for workers to meet skill requirements for tasks and customer demand. While the model can be used in a number of ways, in this paper it is used to generate a worker assignment schedule for cross-trained workers in a dedicated lean manufacturing cell in an electronics assembly plant and to evaluate the effect of increased cross-training on the cell. The resulting worker assignment schedules for the current state and several alternative scenarios for the cell are evaluated using cost results from the optimization model and from a simulation model to assess additional performance metrics. These results demonstrate the usefulness of the worker assignment model and indicate that moderate increases from current cross-training levels are not beneficial for this cell.     

Aligning manufacturing flexibility with environmental uncertainty: Evidence from high-technology component manufacturers in Taiwan

While flexibility improvement is among the top concerns of manufacturing managers, managers are advised to choose the dimensions of flexibility they want in their plants. This study investigates the strategic choice of aligning flexibility development with the external environment that manufacturing managers face. Considering the nature of the high-technology industry in Taiwan, we measure environmental uncertainty based on the dimensions of customer demand, supply, competitors and product technology. Empirical data were collected from manufacturing firms in Taiwan. We then applied path analysis to examine the effect of aligning three types of flexibility: product mix, new product and volume with specific dimensions of environmental uncertainty. The results indicate that the matching of manufacturing flexibility with environmental uncertainty is necessary to ensure profit and sales performance. When faced with certain environmental stimuli, management should choose to emphasize and develop particular manufacturing flexibility.     

Model for flexibility evaluation in manufacturing network strategic planning

In response to market pressures, manufacturers have adopted different approaches to provide flexibility regarding several aspects. In this paper, we suggest a model for the evaluation of the flexibility of the manufacturing supply chain, based on graph theory techniques. This model defines maximum excess demand that may be met using flexibility. Recourse to flexibility enablers is determined based on cost minimisation. Such enablers are volume flexibility, mix flexibility and safety stocks. The proposed model is solved using a two-step Mix Integer Linear Programme; the first step consists in defining maximum demand that may be met while the second step concerns minimising cost. The main benefit of our model is to deal with realistic problems in a rather short time. Therefore, it can be used in a wide ‘what-if’ design process. It means evaluating various contemplated flexibility configurations in multiple demand scenarios in order to choose the best option. It can be also used during operational supply chain planning in order to face to an unbalanced situation. This paper ends with a numerical example illustrating our model’s efficiency.     

Delphi study on supply chain flexibility

The flexibility literature is dominated by research on manufacturing flexibility. More recently, supply chain flexibility has been recognized as an important flexibility construct for meeting customer demand. An Internet-based Delphi study involving a group of expert practitioners is used to enumerate the characteristics, and the importance of those characteristics, in making a supply chain flexible. Expert opinion is one method for gathering information that can be used to develop a model of supply chain flexibility and provide a framework for future research.     

客户参与下的服务型制造系统模型

客户参与的产品服务系统是服务型制造的一个显著特征。针对客户参与度对实施服务型制造的企业产品服务系统绩效难以度量的难题,以客户参与度为变量,构建了客户参与度与客户满意度、市场需求和企业利润的模型。通过分析表明：客户参与产品服务系统能在一定条件下提升客户满意度,实现市场需求和企业利润的增长;并可用平衡积分卡理论诠释四者之间相互支撑的逻辑关系,最后算例验证了上述模型和理论分析的科学与有效性。     

Customer demand prediction of service-oriented manufacturing incorporating customer satisfaction

With the emergence of individualised and personalised customer demands, the interaction of service and product has come into the sight of manufacturers and thus promoted the arising of service-oriented manufacturing (SOM), a new business mode that combines manufacturing and service. Be similar to the conventional manufacturing, the customer demand prediction (CDP) of SOM is very important since it is the foundation of the following manufacturing stages. As there are always tight and frequent interactions between service providers and customers in SOM, the customer satisfaction would significantly influence the customer demand of the following purchasing periods. To cope with this issue, a novel CDP approach for SOM incorporating customer satisfaction is proposed. Firstly, the structural relationships among customer satisfaction index and the influence factors are quantitatively modelled by using the structural equation model. Secondly, to reduce the adverse effect of multiple structural input data and small sample size, the least square support vector mechanism is employed to predict customer demand. Finally, the CDP of the air conditioner compressor which is a typical SOM product is implemented as the real-case example, and the effectiveness and validity of the proposed approach is elaborated from the prediction results analysis and comparison.     

Operational tactics and tenets of a new manufacturing paradigm ‘instant customerisation’

An increasing trend towards a new manufacturing paradigm of ‘instant customerisation’ is occurring due to customers demanding their orders for customised products or services be fulfilled under zero customer lead time and at a price near the price of mass production. By means of the manufacturing paradigm innovation model (MPIM), the operational tactics, operational tenets, and an operational framework of instant customerisation are elicited and described. An important new tactic within all the operational tactics is finalise-to-individual demand forecasting, meaning end products are finalised according to the forecasting of individual customer's needs. The knowledge and information, which is the primary input of individual demand forecasting, is gleaned and understood by total customer participation and value fusion. Total customer participation and value fusion are developed through customer participation and customer relationship management, which have critical distinctions. The operational framework, which is termed manufacturing paradigm tree of instant customerisation, can characterise the operational tenets, the relationships between different operational tactics and the objectives, and the relationships among different operational tactics. With the proposed framework, instant customerisation can be understood more effectively and holistically.     

A data-driven approach for the optimisation of product specifications

In order to develop the profit-maximising, market share-maximising or cost-minimising bundle of product engineering specifications with proper performance levels, an optimisation model driven by operating data is proposed. The operating data are input as the sources to conduct the optimisation and a data-based customer satisfaction function can be formed. Then, a customer choice model developed from the customer satisfaction is constructed to estimate the customer choice probability. The expected market share (EMS) then can be derived from the choice probability. After all, a multi-objective model is constructed to maximise the EMS and minimise the total engineering cost. The candidate Pareto-optimal solutions can be obtained by solving the optimisation model. Then a membership function is defined to select the optimal solution from the Pareto-optimal solutions. A case study for optimising the smartphone’s specifications is conducted to demonstrate the effectiveness of the newly developed approach. Compared with the commonly used Conjoint Analysis (CA) method in determining the most desired levels for product specifications, the proposed data-driven method can avoid the situation where the user’s preferences are irrational, making the proposed method be more practical in measuring customer preferences than the utility-based model.     

Empirical relationships between some manufacturing practices and performance

Intense global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing manufacturers to adopt manufacturing practices and competitive priorities that enable them to deliver high quality products in a short period of time. Identifying manufacturers’ competitive priorities and effective manufacturing practices has long been considered one of the key elements in manufacturing strategy research. This paper presents the results of a study conducted to identify some of the effective manufacturing practices that have a significant influence on manufacturing performance. This study also identifies the main competitive objectives of manufacturing industries that participated in the study. The results reported in this paper are based on data collected from a survey using a standard questionnaire administered to 1000 manufacturers in Australia. Evidence indicates that product quality and reliability are the main competitive factors for manufacturers and price has become surprisingly a relatively less important factor. Results show that simultaneous pursuit of advanced quality practices can neutralize the potential negative impacts of manufacturing difficulties and significantly improve product quality and manufacturing performance. Failure mode and effect analysis (FMEA) is shown to be an important tool for improving product quality and on time delivery performance. FMEA practice driven by the intention to improve customer satisfaction is more effective than that practised to fulfil customer requirements. Effective supplier relationships are shown to contribute positively to the manufacturing performance. The results also suggest that maintaining a supplier rating system and product data management and regularly updating them with field failure and warranty data are important manufacturing practices.     

Modelling and analysis for sequentially optimising production,maintenance and delivery activities taking into account product returns

This paper develops and analyses a stochastic optimisation problem with a service level constraint for generating a sequentially optimal plan of production, maintenance and delivery activities in a deteriorating manufacturing system. Stochastic demand along with product returns are both assumed the latter of which allows for restocking products returned by the customer which are still new and thus in saleable condition. A constrained production/maintenance/delivery problem with service level, stochastic demand, delivery time, failure rate and product returned is formulated based on quadratic model. This quadratic formulation is adapted to provide an inventory, delivery, production and maintenance policies. The objective of this paper is to study the delivery time influence on the planning of the production, maintenance and delivery activities. Finally, we present simulation results to illustrate the exploitation of the proposed approach.     

A decomposition method for multi-product kanban systems with setup times and lost sales

We consider kanban controlled production systems with three or more different products processed on a single manufacturing facility. Customers for a product arrive according to a Poisson process. If a customer's demand cannot be met from stock, the customer leaves and satisfies his demand elsewhere (lost sales). Between the production of different products setup changes must be performed that take a significant time. Setup times and processing times are product-specific and follow exponential distributions. A production run continues until the target inventory level given by the number of kanbans for the product has been reached (exhaustive processing). Then the manufacturing facility is set up for the next product according to a fixed setup cycle. The exact model is mathematically intractable even for smaller systems. Therefore, we propose a decomposition-based approximation method for estimating steady-state performance measures     

支持大批量定制的Web2．0技术

大批量定制正在成为制造业的主流生产模式．本文研究表明Web2．0技术特点与大批量定制的需求能够较好的吻合,例如,Web2．0技术能够帮助企业提高客户需求获取能力,以便为客户提供更好的个性化服务;Web2．0技术能够更有效地支持企业间的零部件资源共享,以便降低产品成本,缩短交货期;Web2．0技术能够支持标准协同建设,提高企业的协同能力,促进产品的模块化．     

Supply chain design to guarantee quoted lead time and inventory replenishment: model and insights

Do lead time constraints only lead to re-think and re-optimise the inventory positioning along the supply chain or can they impact on the design of the supply chain itself? To answer such a question, we integrate the lead time constraints in a multi-echelon supply chain design model and challenge the difficulty of combining in the same model the long-term decisions (facility location, supplier selection) with the midterm decisions (inventory placement and replenishment, delivery lead time). The model guarantees the respect of the quoted lead time associated with each customer order and the replenishment of the different stocks (raw materials, intermediate and final products) in the different stages of the supply chain between any pair of consecutive orders. We use the model to investigate the impact of the quoted lead time and customer’s order frequency on supply chain design decisions and costs. Some of our results indicate that the lead time constraints can lead to bringing the sites of manufacturing and distribution close to the demand zone and to select local suppliers in spite of their higher cost.     

Evaluation of Product and Process Design Robustness

Critical design decisions are commonly made throughout the product development process assuming known material and process behavior. However, stochastic variation during manufacture can inadvertently result in inferior or unacceptable product performance and reduced production yields. Stochastic simulations have been developed to estimate the end-use performance distribution prior to the commitment of hard tooling. This article proposes a definition for integrated product and process robustness, and extends existing stochastic methods to model the important role of the manufacturing flexibility in elimination of defects and product optimization. The goal is to enable the designer to understand and account for not only the negative effects of manufacturing variation, but also the positive impact of manufacturing flexibility wherein instantaneous corrections in the manufacturing process can frequently improve the product quality and eliminate flaws in the product design. Then, a methodology is introduced and contrasted with conventional development methods in the evaluation of best practices for development of a molded plastic component.     

支持顾客细分策略的用户需求分析方法研究

通过对产品的使用过程进行分析 ,提出了用户需求可表示为用户、环境及操作的函数 ,并且指出全面地获取用户需求的关键在于从用户、环境、操作三个维度扩展需求空间。这种方法能够有效地支持新兴的规模定制生产模式所要求的顾客细分策略 ,并对需求分析阶段的产品建模具有重要的意义。     

A real-options-based analysis for supply chain decisions

Flexibility allows firms to compete more effectively in a world of short product life cycles, rapid product development, and substantial demand and/or price uncertainty. We develop a supply chain model in which a manufacturing firm can have the flexibility to select different suppliers, plant locations, and market regions and there can be an implementation time lag for the supply chain operations. We use a real options approach to estimate the value of flexibility and to determine the optimum strategy to manage the flexibility under uncertainty in the currency exchange rate. To price the operational flexibility, we develop a Monte Carlo simulation technique that is able to incorporate a large number of variables into the valuation. We show that without considering time lag impact, the value of the operational flexibility can be significantly overestimated.