A delayed demand supply chain: Incentives for upstream players

We study a decentralized supply chain where only delayed market demand information is available for making replenishment decisions. The impact of this delay is quantified in a serially linked two-level supply chain where each player exploits the order-up-to replenishment policy. The market demand is assumed to be a first-order autoregressive process. It is shown that the first level of the supply chain benefits from shorter time delays; however, the benefit for the second level is quite minor at best and can sometimes even be (counter-intuitively) detrimental. We conclude that the second level does not have a strong incentive to reduce the time delays in the shared market demand information.     

The Role of Culture as Driver of Quality Management and Performance: Infrastructure Versus Core Quality Practices*

Increasingly, scholars and practitioners recognize the importance of understanding organizational culture when implementing operations management practices. This study investigates the relationships among organizational culture, infrastructure and core quality management practices, and manufacturing performance using two alternative models. Understanding these relationships is important because culture can provide insight into the context dependence of quality management practices and shed light on the mixed results of past studies concerning the link between quality management and performance. Analysis of manufacturing plants from six countries indicates that organizational culture has a stronger influence on infrastructure quality management practices than on core quality management practices, regardless of whether the plants are located in Eastern or Western countries. In addition, infrastructure quality management practices have a significant effect on manufacturing performance. These results contribute to the quality management literature by emphasizing the importance of accounting for culture when making decisions to implement quality management practices to achieve a performance advantage. Finally, we also contribute to the literature on the culture–performance linkage by finding support for a direct link between culture and manufacturing performance.     

An efficient generalized network-simplex-based algorithm for manufacturing network flows

Fang and Qi (Optim. Methods Softw. 18:143–165, 2003) introduced a new generalized network flow model called manufacturing network flow model for manufacturing process modeling. A key distinguishing feature of such models is the assembling of component raw-materials, in a given proportion, into an end-product. This assembling operation cannot be modeled using usual generalized networks (which allow gains and losses in flows), or using multi-commodity networks (which allow flows of multiple commodity types on a single arc). The authors developed a network-simplex-based algorithm to solve a minimum cost flow problem formulated on such a generalized network and indicated systems of linear equations that need to be solved during the course of the network-simplex-based solution procedure. In this paper, it is first shown how various steps of the network-simplex-based solution procedure can be performed efficiently using appropriate data structures. Further, it is also shown how the resulting system of linear equations can be solved directly on the generalized network.     

The Use of Flexible Manufacturing Capacity in Pharmaceutical Product Introductions*

This work considers the value of the flexibility offered by production facilities that can easily be configured to produce new products. We focus on technical uncertainty as the driver of this value, while prior works focused only on demand uncertainty. Specifically, we evaluate the use of process flexibility in the context of risky new product development in the pharmaceutical industry. Flexibility has value in this setting due to the time required to build dedicated capacity, the finite duration of patent protection, and the probability that the new product will not reach the market due to technical or regulatory reasons. Having flexible capacity generates real options, which enables firms to delay the decision about constructing product‐specific capacity until the technical uncertainty is resolved. In addition, initiating production in a flexible facility can enable the firm to optimize production processes in dedicated facilities. The stochastic dynamic optimization problem is formulated to analyze the optimal capacity and allocation decisions for a flexible facility, using data from existing literature. A solution to this problem is obtained using linear programming. The result of this analysis shows both the value of flexible capacity and the optimal capacity allocation. Due to the substantial costs involved with flexibility in this context, the optimal level of flexible capacity is relatively small, suggesting products be produced for only short periods before initiating construction of dedicated facilities.     

Business Location Decisions in the United States: Estimates of the Effects of Unionization,Taxes, and Other Characteristics of States

This article examines how corporate decisions about the location for a new manufacturing plant in the U.S. are influenced by unionization, taxes, and other characteristics of states. The conditional logit model is used with some modifications to make the model more applicable to the business location decision. The most important finding is that the union sympathies of states have a major effect on business location. The results also indicate that state taxes affect business location, contradicting the conventional wisdom in the economic literature, although the tax effect is of modest magnitude.     

Multiple dependent state repetitive sampling plans based on one-sided process capability indices

In this research, multiple dependent state and repetitive group sampling are used to design a variable sampling plan based on one-sided process capability indices, which consider the quality of the current lot as well as the quality of the preceding lots. The sample size and critical values of the proposed plan are determined by minimizing the average sample number while satisfying the producer's risk and consumer's risk at corresponding quality levels. In addition, comparisons are made with the existing sampling plans [Pearn and Wu (2006a Pearn, W. L., and C. W. Wu. 2006a. Critical acceptance values and sample sizes of a variables sampling plan for very low fraction of defectives. Omega: International Journal of Management Science 34 (1):90–101.[Crossref], [Web of Science ®] , [Google Scholar]), Yen et al. (2015 Yen, C. H., C. H. Chang, and M. Aslam. 2015. Repetitive variable acceptance sampling plan for one-sided specification. Journal of Statistical Computation and Simulation 85 (6):1102–16.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar])] in terms of average sample number and operating characteristic curve. Finally, an example is provided to illustrate the proposed plan.     

中国制造业研究与开发资本存量测算

《中国国民经济核算体系（2016）》（Chinese System of National Accounts 2016,CSNA2016）修订了固定资本形成总额的核算范围和核算分类,将能为所有者带来经济利益的研究与开发（Research and Development, R&D）支出纳入固定资本形成总额的核算范围。基于《2008国民账户体系》（System of National Accounts 2008,SNA2008）的GDP核算平台,本文构建了制造业R&D支出的资本化核算框架,测算了中国1990-2016年26个制造业行业的R&D投资与资本存量,为进一步探究制造业无形资产的资本回报率、生产率等经济问题提供了数据支撑。测算结果显示：○1R&D投资是测算R&D资本存量的准确指标。直接使用各行业R&D经费内部支出作为R&D投资,将高估各行业R&D资本存量;○2本文构造的R&D投资价格指数通过了稳健性检验,说明使用城镇居民消费价格指数作为R&D工资支出的价格缩减指数是有效的;○3中国制造业研发实力不断增强。制造业R&D资本存量占全国R&D资本存量的比例从1990年的35.33%增长到2016年的67.75%;高技术制造业的R&D资本存量年均增长率高达20%~22%,对中国经济实现提质增效、转型升级起到重要的支撑和带动作用。     

Some further results on minimum distribution cost flow problems

Manufacturing network flow (MNF) is a generalized network model that can model more complicated manufacturing scenarios, such as the synthesis of different materials to one product and/or the distilling of one material to many different products. Minimum distribution cost flow problem (MDCF) is a simplified version of MNF optimization problems, in which a general supplier wants to proportionally distribute certain amount of a particular product from a source node to several retailers at different destinations through a distribution network. A network simplex algorithm has been outlined in recent years for solving a special case of MDCF. In this paper, we characterize the network structure of the bases of the MDCF problem and develop a primal simplex algorithm that exploits the network structure of the problem. These results are extensions of those of the ordinary network flow problems. In conclusion, some related interesting problems are proposed for future research. This research is partially supported by the National Natural Science Foundation of China (No. 10371028) and a grant from Southern Yangtze University (No. 0003182).     

A Comparison between Basic Cyclic Scheduling and Variable Cyclic Scheduling in a Two‐stage Hybrid Flow Shop

In this paper the impacts of two types of repetitive scheduling systems on the makespan in a two‐stage hybrid flow shop, which consists of one machine in the first stage and multiple process lines in the second stage, are compared. First, we analyzed, through a simulation, how the makespan is affected by the setup frequency and sequencing rules for products under two types of scheduling systems: One is repetitive scheduling with only one batch per product family per scheduling cycle (basic cyclic scheduling system). The other is repetitive cyclic scheduling with various batches per product family per scheduling cycle (variable cyclic scheduling system). Second, we compared which scheduling system is superior under various manufacturing situations. The following points were noted. (1) The superior scheduling system can be shown by a two‐dimensional diagram of the setup frequency and the imbalance in workload for processing among process lines in the second stage. (2) Variable cyclic scheduling is superior in comparison with basic cyclic scheduling when there is a large imbalance in the workload to be processed among process lines in the second stage, or the workload in the second stage is larger than that in the first stage. The result of this research provides guidelines for selecting which scheduling system should be adopted.     

Order Dispatching and Labor Assignment in Cellular Manufacturing Systems

Although order and labor dispatching in the job shop manufacturing setting have been investigated extensively over the last three decades, its representation of actual processes found in practice today is limited due to the move to cellular manufacturing (CM). Manufacturing cells have become an important approach to batch manufacturing in the last two decades, and their layout structure provides a dominant flow structure for the part routings. The flow shop nature of manufacturing cells adds a simplifying structure to the problem of planning worker assignments and order releases, which makes it more amenable to the use of optimization techniques. In this paper we exploit this characteristic and present two mathematical modeling approaches for making order dispatching and labor assignment/reassignment decisions in two different CM settings. The two formulations are evaluated in a dynamic simulation setting and compared to a heuristic procedure using tardiness as the primary performance measure. The formulations are superior to the heuristic approach and can be incorporated into detail scheduling systems that are being implemented by corporations employing enterprise resource planning (ERP) systems today.