A perishable inventory model with Markovian renewal demands

In the inventory model, people usually assume that the inter-demand time is independently identical distributed which may not be true in reality. Here we study an (s,S) continuous review model for items with an exponential random lifetime and a general Markovian renewal demand process. By constructing Markovian renewal equations, we derive the mean and the variance of the reorder cycle time and lead to a simple expression for the total expected long run cost rate. The numerical results illustrate the system behavior and lead to managerial insights into controlling such inventory systems.     

Modeling and simulation of order-driven planning policies in build-to-order automobile production

In adopting build-to-order order fulfillment systems, automotive companies strive to better synchronize their production output with market demand. This essentially gives rise to a new paradigm in production planning. Since all business is linked to customer orders, the operational performance is substantially determined by order-driven planning. Therefore, a clear understanding of the associated planning tasks, order promising and master production scheduling, as well as their dynamic interaction is essential. Based on the analysis of the decision situation of order-driven planning in build-to-order settings, we provide a framework comprising separate interlinked quantitative models for order promising and master production scheduling. The focus of the contribution is on the modeling and evaluation of both models in a dynamic setting. The approach is evaluated by means of a simulative analysis using empirical data from the automotive industry. Conclusions regarding the potentials of such systems with respect to customer service, the leveling of resource utilization, and holding are presented.     

资源环境视角下的企业清洁生产体系研究

在简要回顾清洁生产提出背景和研究现状的基础上,提出基于企业生产构成要件的清洁生产体系,包括技术体系、组织和管理体系、产品体系、外部支持体系,以及针对清洁生产的运行质量和政府政策绩效的资源环境评价体系和政策绩效评估体系。以此促进相应的市场机制建设、政府政策措施以及科学考评机制等关系现有生产方式变革的重点难点问题的解决。     

Broadband achievement index: Moving beyond availability

High-speed access to the Internet enhances economic prosperity, social development and global competitiveness. Significant progress has been made in broadband deployment in the last decade. Nevertheless, there are increasing gaps in broadband adoption, use and speed between, as well as within, the states. Federal and state legislators and regulators currently use a number of indicators such as adoption, availability and speed to track states’ progress in broadband diffusion in order to design appropriate policy responses. Single indicators, however, when analyzed individually, fall short of capturing multi-dimensional aspects of broadband diffusion and, thus, do not provide an integrated and easily comprehensible picture of states’ advancement. To monitor states’ overall progress it is useful to aggregate various indicators into a composite index that could measure the overall extent of broadband diffusion. A composite index can also provide with an important benchmark for designing policies to improve states’ overall performance. This paper offers a flexible framework for benchmarking states’ achievement in broadband diffusion by proposing a composite Broadband Achievement Index (BAI). The index combines several key performance indicators: broadband availability, adoption, competition, speed and the dispersion of broadband adoption within the states utilizing FCC's Form 477 data and the recently collected census block level broadband availability data from NTIA. The purpose is to provide a more comprehensive picture of where the states stand in their evolution toward high-performance America by measuring each state's current broadband achievement relative to other states and providing an important benchmark for assessing state-specific needs. The indicators are combined using the Benefit of the Doubt (BOD) methodology (Cherchye, Moesen, & Van Puyenbroeck, 2004). The methodology is founded on the premise that, absent a consensus on social policy priorities, that are, on which indicators are more important and should be given higher weights in the index, each state is granted leeway for deciding how to weigh its own indicators and the most favorable weights for indicators are determined for each state. A good relative performance in a particular dimension is seen as revealed evidence of setting high state policy priority to that indicator, when each state's specific policy priorities are unknown. Additionally, the Second Order Stochastic Dominance (SOSD) methodology is used to compare the dispersion of adoption in the states. Using SOSD the states are ranked under the assumption that proportionally higher and more equally distributed adoption rates are better.     

Loop-based strategic decision support systems

This paper gives an introduction to a recently developed strategic decision support methodology, which makes it possible to represent rule-setting and rule-fulfilling decision-making processes in companies with their structural and behavioral differences. This new methodology also allows us to simulate evolutionary processes in company systems based on these two forms of decision-making. The new strategic decision support methodology combines the continuous feedback loop concept of system dynamics with discontinuous logical loops, which we call spiral loops. The spiral loop concept, which is based on new developments in evolutionary theory and in the field of artificial intelligence, is used to represent the rule-setting strategic decisions, which generate qualitative change and evolution. The continuous feedback loop concept is used to model the rule-fulfilling policy decisions of companies, which can generate quantitative changes in interaction processes. In order to demonstrate how loop-based strategic decision support systems work in principle we show the ‘portfolio simulation model,’ which helps us to explain and to design the evolution of multibusiness firms in duopoly markets.     

连铸机二冷水模型应用研究

为了提高连铸生产的自动化控制水平,提升浇铸效率和铸坯质量,对唐钢中厚板1#板坯连铸机二冷水模型进行了研究和应用,根据不同钢种的高温力学特性和极限应力范围,制定出不同钢种在各区段适宜的温度区间,对铸坯传热方程进行一维划分,应用有限元方法求解,根据不同的铸坯尺寸、钢种成分、中包过热度和拉速等,实时计算铸坯各位置的温度和凝固状态,动态显示两相区和凝固末端位置等浇铸关键参数,动态调节各区水量,根据现场实际生产需要,开发多种控制模式。经过实际生产测试,模型控制各项指标均满足生产要求,可有效降低人工干预,提升生产效率和铸坯质量,使铸坯在各区所受应力低于极限应力,减少裂纹产生的概率,为高效连铸的实施提供了必要的模型控制基础。     

The assessment of Government support for industrial research: lessons from a study of Norway

Abstract: This paper summarises the results of a recent study carried out by the Science Policy Research Unit for the Norwegian Royal Commission on Industrial Research (the 'Industriforskningsutvalget'). We assess in broad terms the effectiveness of existing Norwegian mechanisms for supporting Industrial research in institutes and firms, focussing in particular on the mechanical engineering and electronics sectors. A range of evaluation techniques are utilised in examining (a) research institute performance, (b) the research institute/industry interface, and (c) the general mode of operation of the funding system. It is suggested that the methodology adopted in the study may be of more general value in evaluating national systems for funding R & D.     

On Reliability Evaluation of Multistate Weighted k-out-of-n System Using Present Value

A new reliability evaluation methodology for multistate weighted k-out-of-n systems is presented in this article. The present value of the cash flow generated by the system components is used as a reliability value. We take a financial view of reliability and consider functioning periods and the time value of money in system reliability analysis. Two approaches, the universal generating function (UGF) and recursive algorithm, are applied to evaluate the reliability of the multistate weighted k-out-of-n system. An illustrative example is calculated based on the proposed system reliability evaluation methodology. It is shown that this evaluation method can also be used to find the value of the maintenance policy. Finally, the UGF and recursive algorithm approaches are compared with each other for large system reliability assessment.     

Optimal flow-line conditions with worker variability

When classical scheduling theory is applied to task sequencing problems, human characteristics are often not the primary consideration and their impact is often assumed away. In this paper, we examine the workforce scheduling problem in sequential flow line systems. We investigate the impact of within-worker and between-worker variability and discuss the selection of scheduling policies between fixed and work-sharing systems. The methodology includes human performance modeling with the objective to maximize throughput with general results with respect to productivity model. We are interested in determining and characterizing the optimal switching time between workers in work-sharing systems. A closed form solution is established in the case of two and three tasks with two workers. For a general number of workers and tasks we establish the maximum number of changes between assignments. We also establish a bound on throughput. Results allow one to solve workforce scheduling problems reduced complexity given the current set of bounds and conditions.     

A VIRTUAL CLASSROOM EXPERIMENT FOR TEACHING ENGINEERING ECONOMY

The productivity of a two-station production line is determined by the station breakdown and repair rates, and by the capacity of the lncerscaclon buffer. A model which describes the station breakdown and repair rates as functions of the maintenance and repair inputs to the system la presented.The production function is Incorporated Into a profit function. The values of maintenance, repair, and an aggregate materials-labor inputs aa well as the capacity of the interstation buffer which maximize profit are sought.     

Autocorrelation in queuing network-type production systems—Revisited

In managing production systems, a strong emphasis is placed on the reduction of variance in specific transformation processes (e.g. for quality control purposes) and on controlling the level of variability in general, as for instance with the Bullwhip effect. However, the possible disturbing interference from autocorrelation (variability dependence over time) in otherwise level stable event streams has received little attention. From the literature, it is known that autocorrelation in queuing systems can lead to a large deterioration in performance compared to an event independent scenario. Thus, either production managers are missing important aspects in production planning, or the ‘realistic’ autocorrelation patterns inherent in actual production setups are not like those considered in the literature. In this paper, relevant and ‘realistic’ types of autocorrelation schemes are characterized and their levels discussed. The paper puts previous works on the impact of autocorrelation in queuing networks in perspective for production systems.     

Taking operations strategy into practice: Developing a process for defining priorities and performance measures

Enterprises’ operations systems and environments, characterized by their complexity and dynamics, are challenging operations strategic management models. The study presented in this paper develops a process to integrate operations strategy content to operations performance measurement system design. Essentially, the developed methodology is based on Process Approach (Cambridge Approach) technique that systematizes procedures for generating a performance measures set coherent to operations strategy objectives and also produces a consistent strategy implementation process. To illustrate the development and the application of the proposed design methodology, findings of two case studies related to telecom engineering services companies are used. Results are discussed focusing on testing the proposed methodology in terms of its feasibility, usability, and utility. A refined process, organized in phases, steps, and procedures, is the final result of the presented study.     

How accurate is the integrated vendor–buyer continuous model?

The classic single-item, deterministic-demand, integrated vendor–buyer model is revisited. The decision problem may also be viewed as that of one centralized firm, dealing with a two-level EOQ-like supply chain with finite production rates. It is sought to optimize the production lot-size and the integral number of its shipments, in equal batches, from the vendor to the buyer. While the problem calls for discrete optimization techniques, we introduced a continuous model where one can take derivatives with respect to both variables. In this short paper, we establish a 98.5% lower bound on the accuracy of this continuous model.     

Probabilistically constrained models for efficiency and dominance in DEA

This paper proposes a stochastic model for data envelopment analysis (DEA), based on the theory of joint probabilistic constraints, which can be used with general multivariate distribution functions. The key assumption is that the random variables representative of the uncertain data follow a discrete distribution or that a discrete approximation of continuous distribution is available. Under this assumption, mixed integer linear models are formulated to tackle, rather originally, dependencies among DMUs inputs, outputs and inputs–outputs through the theory of joint probabilistic constraints. The features of the model are illustrated through an application for the performance evaluation of screening units.     

Integrated product specifications and productivity decision making in unreliable manufacturing systems

This paper considers joint production control and product specifications decision making in a failure prone manufacturing system. This is with the knowledge that tight process specifications, while leading to a product of more reliable quality and higher market value, are at the same time associated with higher levels of non-conforming parts, a higher rate of parts rejection and thus a lowering of overall plant productivity. The decision making is further complicated by the lack of reliability of the production process, which imposes that an adequate, also to be designed, level of inventory of finished parts be maintained. The overall optimal decision policy is defined here as one that maximizes the long term average per unit time profit of a combined measure of quality and quantity dependent sales revenue, minus inventory and backlog costs, in the presence of random plant failures and random repair durations. Policy optimization is achieved via a revisited model of the Bielecki–Kumar theory for Markovian machines and a simulation and experimental design based methodology for the more general cases.     

Vendor performance with supply risk: A chance-constrained DEA approach

The strategic importance of vendor evaluation is well established in the purchasing literature. Several evaluation methodologies that consider multiple performance attributes have been proposed for vendor evaluation purposes. While these techniques range from scoring models that utilize prior articulation of weights to derive composite scores for vendors to advanced mathematical models, methods that incorporate the inherent variability in vendor's performance attributes have been limited. The primary reason for the lack of development of such models is due to the complexities associated with stochastic approaches. In order to more accurately evaluate the performance of vendors, it is critical to consider variability in vendor attributes. This paper is an attempt to fill this void in vendor evaluation models by presenting a chance-constrained data envelopment analysis (CCDEA) approach in the presence of multiple performance measures that are uncertain. Our paper effectively demonstrates the first application of CCDEA in the area of purchasing, in general, and vendor evaluation, in particular. The model is demonstrated by applying it to a previously reported dataset from a pharmaceutical company.     

An evaluation of the Connected Nation broadband adoption program

Closing the digital divide and increasing broadband adoption within households and communities continues to be a target for government and nonprofit groups. While a large number of studies have examined policies and programs aimed at improving broadband infrastructure availability, little analysis to date has focused on evaluating efforts to increase adoption. One of the most well-known programs focused on adoption is Connected Nation, which partnered with 14 states to provide local curricula aimed at raising residential connection rates. This analysis uses a generalized difference-in-difference methodology to evaluate the effectiveness of the Connected Nation program in 5 states during 2012 and 2013. The results indicate that participation in the Connected Nation program had no significant impact on broadband adoption rates. This paper represents a rigorous evaluation of one of the most well-known adoption-oriented programs and emphasizes that measurable impacts of such efforts may not accrue over the short term.     

Relief system design scope of CCPS effluent handling guidelines

The forthcoming CCPS Guidelines for Effective Handling of Emergency Release Effluents includes the methodology for defining effluent flow rates and characteristics during emergency pressure relief event. The intent is to provide the user with relief systems in a typical process unit without requiring expert assistance or access to other documents. Cases requiring special design training and methodology due to combinations of multi-phase, multi-component, reactive, geometric and thermodynamic complexities are identified and illustrated in the Guidelines. However, the complete design technology for such cases is beyond the scope of these Guidelines; reference is given to applicable documents.     

Approximation approach for the performance analysis of production lines under a kanban discipline

In a JIT production environment, pull-type control systems are usually implemented to reduce the lead time and to synchronize the production rate with the demand rate. The design of an effective production control system requires easy and reliable approaches for evaluating the effect of the major system parameters on its performance.In this paper we model the kanban control system of a manufacturing line as a Markov process. In addition, we develop an approximation approach to the model that permits reliable evaluation of manufacturing system performance in terms of throughput time and work-in-process. The validation of the approach is implemented by comparing the exact results (based on discrete event simulation) and the approximated results.A good approximation is observed for a large range of conditions.     

Reliability evaluation and adjustment of supply chain network design with demand fluctuations

This study focuses on supply chain network design problems by considering economies of scale and demand fluctuations. A reliability evaluation method is developed to evaluate the performance of plants under demand fluctuations. In addition, two mathematical programming models are developed to determine the optimal adjustment decisions regarding production reallocation among plants under different fluctuating demands. The judgments to adjust or to do-nothing are investigated by comparing the results if the adjustment is made or not made. Results show that making adjustments benefits the manufacturers by reducing total production cost and avoiding revenue loss, which outweighs the extra costs, especially for high value-added products. Results also suggest that the manufacturer should ignore a short period abnormal state, since the benefits to respond to it might not compensate the high allocation costs. The results of this study provide a reference for the manufacturer in their decision making process of network planning with demand fluctuations, when they have to cope with benefits and costs during abnormal states.