Optimal production control of a service-oriented manufacturing system with customer balking behavior

The great challenge for service-oriented manufacturing (SOM) is how to cope with customer behavior while making decision on production planning and scheduling. In this paper, we consider a single-stage manufacturing system for SOM with impatient customers. In order to represent customer balking behavior caused by backlog, we employ a balking function, which is an arbitrary non-decreasing function of the backlog for characterizing the customer’s response to the backlog. The objective is to find the optimal production policy that minimizes the system cost. The problem is formulated as a Markov decision process. The optimal production policy is proved to be a base-stock policy. The effects of system parameters on the optimal base-stock level are analytically investigated, and the impact of customer balking behavior on the system is illustrated by numerical example in which linear balking function is employed. Numerical example shows that customer balking has a significant impact on the optimal control and the performance measures of the system under the optimal policy.     

Sustainability in Supply Chain Management: Aggregate Planning from Sustainability Perspective

Supply chain management that considers the flow of raw materials, products and information has become a focal issue in modern manufacturing and service systems. Supply chain management requires effective use of assets and information that has far reaching implications beyond satisfaction of customer demand, flow of goods, services or capital. Aggregate planning, a fundamental decision model in supply chain management, refers to the determination of production, inventory, capacity and labor usage levels in the medium term. Traditionally standard mathematical programming formulation is used to devise the aggregate plan so as to minimize the total cost of operations. However, this formulation is purely an economic model that does not include sustainability considerations. In this study, we revise the standard aggregate planning formulation to account for additional environmental and social criteria to incorporate triple bottom line consideration of sustainability. We show how these additional criteria can be appended to traditional cost accounting in order to address sustainability in aggregate planning. We analyze the revised models and interpret the results on a case study from real life that would be insightful for decision makers.     

An optimization approach for designing routes in metrological control services: a case study

This paper is the first to tackle the problem of designing routes in service companies that are responsible for the metrological control of measuring equipments at customer sites. This real-world problem belongs to the well-known Rich Vehicle Routing Problems which combine multiple attributes that distinguish them from traditional vehicle routing problems. The attributes include fixed heterogeneous fleet of vehicles, time windows for customers and depot, resource synchronization between tours, driver-customer and vehicle-customer constraints, customer priorities and unserved customers. This routing and scheduling problem is modeled with linear programming techniques and solved by a variable neighborhood descent metaheuristic based on a tabu search algorithm with a holding list. A real-life case study faced by a company in the region of Andalusia (Spain) is also presented in this work. The performance of the metaheuristic is compared with the literature for the standard fixed heterogeneous vehicle routing problem. Results obtained on a real case instance improve the solutions implemented by the company.     

A heuristic based batching and assigning method for online customer orders

In an online order picking system, customer orders arrive in real time and the picking information is updated dynamically. One challenging problem is how to process customer orders in a timely manner. In this paper, a nonparametric heuristic method, Green Area, is presented to address the real-time online order batching problems. By nonparametric, we mean that our method is independent of the parameters of a warehouse layout and the characteristics of customer orders; these parameters facilitates the implementation in real life. The advantages of this method are verified under different scenarios by simulations. Specifically, the influences of the arrival rate, the number of order pickers and the number of orders in the order service time are discussed. The results demonstrate that the Green Area method leads to shorter order service times than traditional methods for optimal batch sizes. Finally, we demonstrate that the Green Area method can be applied to online order picking systems with variable arrival rates.     

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.     

Order quantity flexibility as a form of customer service in a supply chain contract model

This paper analyzes the Quantity-Flexibility (QF) contract, under which the buyer provides to the supplier information about expected future orders for the predetermined horizon and the supplier, in return, provides the buyer with the flexibility to adjust future orders later. Under this scheme, the flexibility profile of the contract can be perceived by the buyer as a form of customer service, by which the supplier commits to fulfil the buyer??s maximum likely order at the cost of the supplier??s inventory risk. The simulation results show that the benefit of the contract to either party clearly depends on the flexibility profile of the contract. For the supplier, there exists a trade-off between customer service level and inventory risk associated with the flexibility profile. However, for the buyer, the flexibility demonstrates a principle of diminishing returns, which is contrary to the general notion that buyers always prefer more order quantity flexibility. In fact, greater flexibility does not always translate into better customer service to buyers.     

Integration of order picking and vehicle routing in a B2C e-commerce context

E-commerce sales are increasing every year and customers who buy goods on the Internet have high service level expectations. In order to meet these expectations, a company’s logistics operations need to be performed carefully. Optimizing only internal warehouse processes will often lead to suboptimal solutions. The interrelationship between the order picking process and the delivery process should not be ignored. Therefore, in this study, an order picking problem and a vehicle routing problem with time windows and release dates are solved simultaneously using a single optimization framework. To the best of our knowledge, it is the first time that an order picking problem and a vehicle routing problem are integrated. A mixed integer linear programming formulation for this integrated order picking-vehicle routing problem (OP-VRP) is provided. The integrated OP-VRP is solved for small instances and the results are compared to these of an uncoordinated approach. Computational experiments show that integration can lead to cost savings of 14% on average. Furthermore, higher service levels can be offered by allowing customers to request their orders later and still get delivered within the same time windows.     

Maximum Entropy Principle Based Estimation of Performance Distribution in Queueing Theory

In related research on queuing systems, in order to determine the system state, there is a widespread practice to assume that the system is stable and that distributions of the customer arrival ratio and service ratio are known information. In this study, the queuing system is looked at as a black box without any assumptions on the distribution of the arrival and service ratios and only keeping the assumption on the stability of the queuing system. By applying the principle of maximum entropy, the performance distribution of queuing systems is derived from some easily accessible indexes, such as the capacity of the system, the mean number of customers in the system, and the mean utilization of the servers. Some special cases are modeled and their performance distributions are derived. Using the chi-square goodness of fit test, the accuracy and generality for practical purposes of the principle of maximum entropy approach is demonstrated.     

Managing perishability in production-distribution planning: a discussion and review

Managing perishability may represent a remarkable problem in supply chain management of a varied set of industries. In fact, perishability can influence, for example, productivity or customer service and it may happen to occur in one or more processes throughout the supply chain. In this paper a review on planning models that handle perishability issues in production and distribution is conducted. The contribution of this paper is three-fold. First, a new framework for classifying perishability models based on multiple process features is presented. Second, it draws the community attention to the importance of managing perishability in many different industries’ supply chains by showing its relevance and by reviewing the literature related to production and distribution planning. Finally, it points towards research opportunities so far not addressed by the research community in this challenging field.     

The Structure and Evolution of Buyer-Supplier Networks

In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf''s law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks – shocks affecting only a particular firm – through customer-supplier chains.     

Bringing science and pragmatism together a tiered approach for modelling toxicological impacts in LCA

Goal, Scope and Background  The EU 5^th framework project OMNIITOX will develop models calculating characterisation factors for assessing the potential toxic impacts of chemicals within the framework of LCA. These models will become accessible through a web-based information system. The key objective of the OMNIITOX project is to increase the coverage of substances by such models. In order to reach this objective, simpler models which need less but available data, will have to be developed while maintaining scientific quality. Methods. Experience within the OMNIITOX project has taught that data availability and quality are crucial issues for calculating characterisation factors. Data availability determines whether calculating characterisation factors is possible at all, whereas data quality determines to what extent the resulting characterisation factors are reliable. Today, there is insufficient knowledge and/or resources to have high data availability as well as high data quality and high model quality at the same time. Results  The OMNIITOX project is developing two inter-related models in order to be able to provide LCA impact assessment characterisation factors for toxic releases for as broad a range of chemicals as possible: 1) A base model representing a state-of-the-art multimedia model and 2) a simple model derived from the base model using statistical tools. Discussion. A preliminary decision tree for using the OMNIITOX information system (IS) is presented. The decision tree aims to illustrate how the OMNIITOX IS can assist an LCA practitioner in finding or deriving characterisation factors for use in life cycle impact assessment of toxic releases. Conclusions and Outlook  Data availability and quality are crucial issues when calculating characterisation factors for the toxicity impact categories. The OMNIITOX project is developing a tiered model approach for this. It is foreseen that a first version of the base model will be ready in late summer of 2004, whereas a first version of the simple base model is expected a few months later.     

患者满意评价指数模型研究

医院是社会文明服务的窗口,医德医风关系到医院和医务人员自身的声誉。患者对于医疗服务的满意度对医院的生存和发展有着重要影响,随着医疗机构之间的竞争愈演愈烈,医疗服务的满意研究受到了更多的重视。患者的满意度与医院忠诚度二者是相辅相成的关系,只有满意的患者才能成为医院的忠诚顾客,再通过这些忠诚顾客的口碑影响其他患者,医院的形象才能得以提升。目前医院患者的满意研究出现了一个特殊的现象：对各类病人的满意研究得出了高的满意率,但社会对医院服务的强烈批评却屡见不鲜。本文分析了目前患者满意评价体系存在的问题,并以服务管理领域顾客满意理论为指导,通过分析患者满意的影响要素以及各要素的相互关系,探讨医院患者满意评价模型构建方法。     

Optimization of workcell layouts in a mixed-model assembly line environment

Mixed-model assembly lines enable automotive manufacturers to build different vehicles using the same equipment and facility. They allow a more rapid response to changes in customer demand. However, the increased production flexibility creates new challenges regarding assembly line planning and balancing. Part of this problem is how to allocate stock within the workcells so that non-value added operations, such as walking and waiting, are minimized. This paper addresses the issue of workstation layout optimization. Different formulations can be used to minimize non-value added time depending on the level of sophistication desired. We present three different optimization formulations and give an example of an optimized workstation layout.     

服务蓝图在出入院服务流程优化中的应用及效果分析

目的 对出入院服务流程进行梳理与优化，提高服务效率、改善患者体验。方法 利用服务蓝图确定住院患者的出入院服务体验、内部服务流程、后台支持保障系统等，并对服务效率和患者体验进行评价。结果 在某三甲综合性医院建立出入院服务中心，统筹协调所有出入院相关服务后，患者术前待床时间、办理出入院手续时间、术前检查等待时间和往返距离，均比去年同期有所降低。结论 将服务蓝图应用于医院出入院服务流程的优化，通过资源合理配置、跨部门协作、信息平台支撑、规章制度保障，能够有效地保障患者安全、提高运行效率、提高患者满意度。     

Effects of feedback of information on clinical practice: a review.

OBJECTIVE--To establish what is known about the role of feedback of statistical information in changing clinical practice. DESIGN--Review of 36 studies of interventions entailing the use of statistical information for audit or practice review, which used a formal research design. SUBJECTS--Papers identified from computer searches of medical and health service management publications, of which 36 describing studies of interventions designed to influence clinical care and including information feedback from clinical or administrative data systems were reviewed. MAIN OUTCOME MEASURES--Evidence for effect of information feedback on change in clinical practice. RESULTS--Information feedback was most likely to influence clinical practice if it was part of strategy to target decision makers who had already agreed to review their practice. A more direct effect was discernable if the information was presented close to the time of decision making. The questions of the optimum layout and quantity of information were not addressed; the 36 papers were insufficient for defining good formats for information to be used for audit or quality assurance. CONCLUSIONS--Given the cost of information processing and the current emphasis on closing the audit loop in the health services, it is important that the use of information in the audit process should be critically evaluated.     

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.     

Some Applications of a Bivariate BOREL-TANNER Distribution

This paper considers the probability distribution of the number of customers served in the busy period of a single server queue with POISSON input and constant service time. Applications to traffic flow, semi-infinite discrete dam and branching processes are described. It is shown that in many situations the bivariate BOREL-TANNER distribution provides a better fit than the bivariate negative binomial distribution.     

Queues with Dropping Functions and General Arrival Processes

In a queueing system with the dropping function the arriving customer can be denied service (dropped) with the probability that is a function of the queue length at the time of arrival of this customer. The potential applicability of such mechanism is very wide due to the fact that by choosing the shape of this function one can easily manipulate several performance characteristics of the queueing system. In this paper we carry out analysis of the queueing system with the dropping function and a very general model of arrival process—the model which includes batch arrivals and the interarrival time autocorrelation, and allows for fitting the actual shape of the interarrival time distribution and its moments. For such a system we obtain formulas for the distribution of the queue length and the overall customer loss ratio. The analytical results are accompanied with numerical examples computed for several dropping functions.     

Uncertainty of global warming potential for milk production on a New Zealand farm and implications for decision making

Background, aim and scope  

As a food exporting nation, New Zealand recognises that the Global Warming Potential (GWP) impact of agriculture has become important to food customers. Food production policy and industry analysts make GWP decisions based on greenhouse gas inventory and life cycle assessment (LCA) results. For decision making, the level of confidence associated with information is important. However, treatment of uncertainty has been problematic in LCA, especially in agricultural systems. In this paper, the GWP of 1 kg of milk was used as a case study to test the feasibility of quantifying uncertainties by Monte Carlo simulation in an LCA applied to an agriculture product. The study also contributes to the development of good practice and has implications for the incorporation of uncertainties into decision making.