An outsourcing decision model for sustaining long-term performance

Outsourcing is a strategically important activity that enables an enterprise to achieve both short and long term benefits. An important but less well researched issue concerns outsourcing in relation to the long-term performance of an enterprise. This paper addresses this issue from the point of view of the protection of core competencies during outsourcing and by considering the trade-off necessary when certain amounts of knowledge transfer/sharing is inevitable. Two major outsourcing decision variables have been identified and quantified—the significance of the component/process technology involved and the risk of disclosing this technology to suppliers. Nine scenarios are generated by considering each of the two variables at three levels of severity: high, medium and low. Each scenario is explored in terms of the appropriate outsourcing approach, the appropriate management of the core competencies/knowledge, and the selection of suppliers. The validity of the outsourcing decision model is established using four products with 861 components from four manufacturing companies based in China.     

Production system design for quality robustness

In automotive assembly plants, vehicles with defects are either repaired (e.g., components are exchanged, scratches are polished, etc.) or reworked (e.g., the whole vehicle is repainted) to maintain high product quality. The performance of vehicle quality is typically characterized in terms of the first time quality and also the quality buy rate. First time quality is defined as the good job ratio of all first time processing jobs, while the quality buy rate is the good job ratio of all processed jobs, including the first time jobs and reworked jobs.

In this paper, we study a repair and rework system at an automotive paint shop with random first time quality. Specifically, we show that paint quality, in terms of quality buy rate, can be described by a function of repair capacity and first time quality. Increasing the repair capacity can improve the quality buy rate and reduce unnecessary repaints. Variations in first time quality may lead to a reduction in the quality buy rate and an increase in unnecessary repaints, and consequently, a substantial waste of production capacity and materials. In addition, we observe that the average quality buy rate depends primarily on the mean and coefficient of variation of the first time quality rather than its complete distribution. Based on these results, we introduce the notion of quality robustness and show that the design of a production system should accommodate randomness in first time quality to achieve a robust quality buy rate. Finally, a case study on a repair and rework system redesign to improve paint quality is presented.     

Incorporating end-user models and associated uncertainties to investigate multiple stakeholder preferences in system design

The essence of systems engineering lies in enabling rational decision-making that is consistent with the preferences of the system’s stakeholders. Modern approaches, such as value-driven design, attempt to convey the true preferences of the stakeholder using mathematical formulations like value models. A critical step to the formation of value models is the identification of the stakeholders. A primary stakeholder must be identified and then it must be determined how the other stakeholders’ preferences impact the preference of the primary, if they do at all. This paper looks at three stakeholders of an electric vehicle system, all of which could be considered the primary stakeholder dependent on the situation. Novel customer, commercial, and government-oriented value models are created. To understand the impact of customers on the primary stakeholder’s designs, an end-user value-based demand model is developed and a method for integrating end-user preferences into the manufacturer’s value model is demonstrated. Uncertainties associated with the end-users, including those associated with the economy, are quantified and incorporated into a value-based design framework through Monte Carlo simulations. Possible stakeholder risk attitudes are discussed and a rational decision-making strategy to maximize stakeholder’s system value under uncertainty is presented. The resulting designs and the influences of the multiple stakeholders are discussed, showing that the identification and incorporation of the important stakeholders are critical to the systems engineering process and value-based design in particular.     

Selecting a near‐optimal design for multiple criteria with improved robustness to different user priorities

In a decision‐making process, relying on only one objective can often lead to oversimplified decisions that ignore important considerations. Incorporating multiple, and likely competing, objectives is critical for balancing trade‐offs on different aspects of performance. When multiple objectives are considered, it is often hard to make a precise decision on how to weight the different objectives when combining their performance for ranking and selecting designs. We show that there are situations when selecting a design with near‐optimality for a broad range of weight combinations of the criteria is a better test selection strategy compared with choosing a design that is strictly optimal under very restricted conditions. We propose a new design selection strategy that identifies several top‐ranked solutions across broad weight combinations using layered Pareto fronts and then selects the final design that offers the best robustness to different user priorities. This method involves identifying multiple leading solutions based on the primary objectives and comparing the alternatives using secondary objectives to make the final decision. We focus on the selection of screening designs because they are widely used both in industrial research, development, and operational testing. The method is illustrated with an example of selecting a single design from a catalog of designs of a fixed size. However, the method can be adapted to more general designed experiment selection problems that involve searching through a large design space.     

Workload prediction for improved design and reliability of complex systems

This paper describes a method and a tool for analysing and predicting workload for the design and reliability of complex socio-technical systems. It concentrates on the need to assess workload early in the design phase to prevent systems failures. This is a continuation of our previous work on workload assessment. The method is supported by a tool that enables scenario-based validation of prospective socio-technical systems designs such as command and control rooms of military vessels. The approach combines probabilistic measures of human performance with subjective estimates of workload. The causal relationships of performance shaping factors (PSF) are modelled in a Bayesian belief network (BBN) and used to assess the agent's operational performance and reliability. Workload for each agent is calculated based on demand placed upon agents in terms of behavioural response to tasks, communications and interactions between humans and technology. The approach uses scenarios to stress test prospective system designs, where each scenario is modelled as a sequence of events. Reliability is expressed in terms of human error and is dynamically assessed throughout test scenario executions using BBN technology. The innovation beyond traditional reliability analysis relies to the use of dynamic and static estimates of reliability inputs for better informed assessment. This method enables identification of performance bottlenecks to be addressed by the designer early in the design phase. A case study is presented that demonstrates the use of the method and tool for the design of the command and control room of a military vessel.     

An information trail model for capturing human behaviour in artefact creation and use in complex work systems

This article presents an information trail model. The model is a method for uncovering information transformation using artefacts in complex work systems. We use a patient care scenario in a hospital emergency department to illustrate theoretical, methodological and design elements of the model. In a complex system, humans create and manage complexity, a paradox. The information trail model proposes that humans manage the paradox by creating and evolving artefacts and information cues. They organise purposefully through self-organisation and stigmergical behaviour. Information trail model states that humans leave trails of information as signs or symbols, and the piecing together and transformation of which will lead to final goals. Information trails contain work attributes and strategies, which can be utilised in work system design.     

Contract design for cooperative product service system with information asymmetry

This paper studies how to effectively provide product service system (PSS) in the supply chain with asymmetric information for service-oriented manufacturing (SOM). With a PSS, the manufacturer chooses the product quality, and the retailer, who possesses private cost information, is responsible for adding necessary value-added service based on the basic product. The analytical underpinnings of our work are provided by the principal-agent paradigm. In the paper, we develop three types of contracts and conduct a detailed comparison among the three contract models. With these studies, we find that: (i) the wholesale price contract is dominated by the other two contracts, (ii) The retail price maintenance contract can always generate a higher profit for the manufacturer and a higher welfare for the consumers, whereas the franchise fee (FF) contract can always generate a higher profit for the retailer and (iii) The FF contract can always stimulate more service from the retailer. Our theoretical and numerical results show that there are significantly different effects when the three types of contracts are utilized in the supply chain for SOM with asymmetric information, and which of them is the most attractive will depend largely on the power structure of the supply chain and/or their cost information types.     

An improved model for simulating impedance spectroscopy

A numerical method for simulating the frequency-dependent impedance response of multi-phase composite materials has been developed. The algorithm takes as input 1) a digital image of a microstructure, in two or three dimensions, of any specified composite material, and 2) the frequency-dependent electrical properties of the individual phases of the composite. An impedance spectrum of any frequency range can then be computed using a conjugate gradient algorithm operating on a finite difference solution scheme of Laplace's equation. Examples are given of the impedance of analytically solvable microstructures, to validate the algorithm, and of a random system, to test the usefulness of two different effective medium theories.     

Optimal acquisition decision in a remanufacturing system with partial random yield information

When making decisions to acquire used products or components (cores), a remanufacturer faces limited information on the quality or proportional yield of cores during the recovery process. In this paper, we propose and analyse a robust optimisation model for studying the remanufacturing decision problem with partial random yield information, that is, when the quality information of cores is partly unknown in a remanufacturing system. Regarding the impacts of unknown yield information, we only require the support and mean of the proportional yield rather than the true distributions. The closed-form solutions of acquisition quantities are derived based on the minimax regret approach. In addition, to validate the effectiveness of the analytical results, particularly the acquisition of yield information, numerical experiments are designed and implemented using (1) the support and mean of the proportional yield based on the manufacturer’s knowledge and (2) a sampling inspection to evaluate the performance of the robust optimisation approach, the benchmark, and the naïve approach. We observe that the minimax regret approach slightly underperforms compared to the benchmark but performs much better than the naïve approach. As an acceptable choice, this approach is less complicated and extremely easy to implement to meet the needs of practical situations based on its robust closed-form solutions.     

采用国际标准的冷冻集装箱性能测试室的改进设计及分析

主要依据国际标准ISO1496-2及ATP协议(国际易腐食品运输及其运输专用装备的协议)改进设计并建造了一个用于冷冻集装箱热工性能测试的试验系统.通过与原试验系统的比较分析,完成了环境室空气处理方案设计、测试用制冷系统的更新配置及温湿度控制方法的调整,并顺利地进行了漏热试验与冷机试验的项目考核.     

An interactive multi-objective algorithm for decentralized decision making in product design

To remain competitive and gain new shares of the market, industries must develop their products quickly while meeting the multiple customer requirements. To reduce product development time, the design step is often accomplished by several working groups working in parallel. These working groups are often decentralized and are supervised by a director. This paper focuses on solving a multi-objective problem in a setting that is called a “decentralized environment.” Collaborative optimization is a strategy used for solving problems in a decentralized environment. This strategy divides a problem into subproblems in order to give more autonomy to working groups, thus facilitating work in parallel. In this paper, collaborative optimization is paired with an interactive algorithm to solve multi-objective problems in a decentralized environment. It can be easily adjusted within the structure of a development process in a given industry and allows collaboration between the director and his/her working groups. The algorithm captures the director’s and the working groups’ preferences and generates several Pareto-optimal solutions. The algorithm was tested on a two-bar structure problem. The results obtained match those published in the literature.     

An information system for village handpumps

The need for a computerised information system for handpumps installed in any state is brought out. A system with organisational and software aspects is presented. The organisational aspect covers the generation and transmission of data on handpumps at the users’ and the government level. The software consists of a Fortran program, data files, an updating program and a transaction file. The periodic updating of data files is discussed. The system output covers many items of vital information needed for formulating maintenance and research and development policies. A test run of the program with an arbitrarily selected data base is discussed.     

一种改进的相机灵敏度测试系统

空间激光通信系统以激光为载体进行数据传输,由于大气信道干扰、剧烈平台扰动、强烈大气附面层等不利影响,使得捕获探测器接收到的光斑信号非常微弱,影响通信链路的建立,对捕获探测器的灵敏度测量有助于分析和评价捕获链路建立的最远距离。在充分分析捕获链路功率的基础上搭建实验系统,用扫描振镜及CCD相机完成对其灵敏度测试实验。实验表明:当曝光时间为2 ms和0.2 ms时,相机的探测能力分别为-80.83 d Bm和-72.43 d Bm。在极限探测灵敏度下,选用高斯拟合算法进行激光光斑中心的定位计算,结果表明该算法定位精度可达0.01pixel,并且具有良好的稳定性。     

An improved steady inverse method for turbomachinery aerodynamic design

An improved inverse method for turbomachinery design is developed in this paper. A strict ‘no-slip’ boundary condition is imposed during the flow time marching process, and a virtual movement velocity is computed based on characteristics boundary conditions according to the difference of specified and calculated pressure loading, then the camber line of the blade is moved accordingly. A new ‘inverse’ time step calculation method is proposed to make the value of the ‘inverse’ time step case-independent, and a coupled non-uniform rational B-spline (NURBS) smoothing technique is used to improve the robustness of the solver, also guarantee the manufacturability of the obtained blade. Two-dimensional test cases, including compressor and turbine cascades, are adopted to validate the method. Then, the method is extended to three dimensions, and a high-loaded rotor of a fan stage is redesigned by the method in a stage environment. The final results indicate a fairly large performance gain, which demonstrates the effectiveness of the improved method.     

An improved monte carlo technique for radiation shield design

Reduction of statistical error in Monte Carlo shielding calculations is achieved by using antithetic variates with geometrical surface splitting while solving the radiation transport problems. Numerical results are presented for sample calculations for slab shields of different dimensions. The present method shows great improvement in efficiency for thick slabs and therefore is useful for practical shielding calculations.     

Conceptual robustness in simultaneous engineering: An extension of Taguchi's parameter design

Simultaneous engineering processes involve multifunctional teams; team members simultaneously make decisions about many parts of the product-production system and aspects of the product life cycle. This paper argues that such simultaneous distributed decisions should be based on communications about sets of possibilities rather than single solutions. By extending Taguchi's parameter design concepts, we develop a robust and distributed decision-making procedure based on such communications. The procedure shows how a member of a design team can make appropriate decisions based on incomplete information from the other members of the team. More specifically, it (1) treats variations among the designs considered by other members of the design team asconceptual noise; (2) shows how to incorporate such noises into decisions that are robust against these variations; (3) describes a method for using the same data to provide preference information back to the other team members; and (4) provides a procedure for determining whether to release theconceptually robust design or to wait for further decisions by others. The method is demonstrated by part of a distributed design process for a rotary CNC milling machine. While Taguchi's approach is used as a starting point because it is widely known, these results can be generalized to use other robust decision techniques.     

An improved MCDM DEA model for technology selection

This paper presents an Improved MCDM Data Envelopment Analysis (DEA) model in order to evaluate the best efficient DMUs in Advanced Manufacturing Technology (AMT). This model is capable of ranking the next most efficient DMUs after removing the previous best one.     

基于分解的复杂机械系统多级设计方法

复杂机械系统的设计涉及众多的设计变量和设计约束,传统的求解方法往往难以或不能获得设计结果。综述了不同工程领域解决复杂问题基于分解的方法,评述了其优缺点,以实例研究了将基于分解的多级设计方法用于复杂机械系统设计的可能性和有效性,并讨论了这一领域中的关键问题和可能的解决途径。