灰关联法在企业并购风险度量中的应用

利用灰色系统理论中的灰关联度分析技术 ,对不同并购方案的风险程度进行比较 ,可以找到风险较低的并购方案 .通过案例分析可知灰关联度量法较模糊度量法更加实用有效     

Modelling and simulation of automated manufacturing systems for evaluation of complex schedules

Automated manufacturing systems have been studied widely in terms of scheduling. As technology evolves, the behaviour of tools in automated manufacturing systems has become complicated. Therefore, mathematical approaches to the analysis of complex schedules no longer reflect reality. In this paper, we propose a systematic way of conducting simulation experiments to evaluate the complex operating schedules of automated manufacturing systems. A simulation model is based on a timed Petri net to take advantage of its mathematical strength. Since a Petri net cannot itself have token firing rules, we introduce additional states called operational states. Operational states are not directly related to a Petri net, and are only used for decision making. In addition, a decision function that is responsible for the conflict resolution of a Petri net model and an operational state transition function are introduced. The parallel simulation concept is also suggested by dividing a Petri net into several independent decision sub-nets. A multi-cluster tool system for semiconductor manufacturing is analysed as an application.     

Simulation of capacity and cost for the planning of future process chains

One of the most promising approaches in modern microelectronics is the introduction of 3D chip micro systems with through-silicon via (TSV) interconnections. A successful transfer of this technology from the scientific level up to the level of mass production is not least of all a matter of cost-effectiveness and profit, which is directly related to high productivity. The developed technologies therefore have to be feasible for effective mass production. In this paper we introduce a method for planning and evaluating costs in future process chains. This method goes beyond usual mostly Excel-supported solutions, as it is based on a discrete event simulation system. The simulation model is generically generated out of an XML process chain definition file and includes a sophisticated state model for machines. Multiple process scenarios are created with the help of a supporting software tool. These scenarios are investigated for achieving favourable equipment and process chain configurations as well as control strategies to support manufacturing ramp-ups.     

Methods for activating the decision-making process that is used for controlling flexible manufacturing systems

This paper deals with controlling flexible manufacturing systems (FMS) operating in volatile production environments. Shnits et al. (Shnits, B., Rubinovitz, J., and Sinreich, D., 2004. Multicriteria dynamic scheduling methodology for controlling a flexible manufacturing system. International Journal of Production Research, 42 (17), 3457–3472.) and Shnits and Sinreich (Shnits, B. and Sinreich, D., 2006. Controlling flexible manufacturing systems based on a dynamic selection of an appropriate operational criteria and scheduling policy. International Journal of Flexible Manufacturing Systems, 18 (1), 1–27.) developed a multi-criteria dynamic scheduling mechanism for controlling an FMS that can cope with such environments. An important part of this mechanism functioning, which impinges directly on its performance, is the activation of its decision-making process. This study continues the research presented in the above-mentioned papers and proposes different triggering methods for activating the control system decision-making process. The operational conditions for each suggested triggering method were analysed and a comparative analysis between these methods was performed. It was revealed that the highly dynamic triggering method, which activates the decision-making process right before a resource becomes available, outperformed the triggering methods that use a predefined scheduling period.     

食品中微生物危害定量风险评估综述

近年来食品安全事件频发,给消费者带来了健康风险,也扰乱了国家经济秩序。在我国,由于食品中微生物危害导致的食品安全问题在总数中占很大比重。微生物危害的定量风险评估,能够帮助政府和企业增强风险管理能力,预防和控制微生物危害,从而提高整体食品安全水平。本文对当前国内外食品中微生物危害的定量风险评估技术的研究现状进行了综述,对现存的问题及未来的发展趋势进行了分析。     

A model based approach to assess the performance of production systems in degraded mode

Nowadays production systems are asked to perform their activities in a high uncertainty environment and to guarantee their performance in this environment. Therefore, they are asked to master risks that are part of their daily activities, to maintain the performance which is considered as their key success factor. Risks may cause serious effects that threaten the production systems and degrade their performance. Nevertheless, we cannot estimate the degradation that a risk may cause to system performance, since risk analysis methods found in the literature do not allow simulating the behaviour of the system in degraded mode. In order to help production systems to assess their performance in risk situations, we propose in this paper a model-based approach that enables assessing the performance of production systems in degraded mode. Our approach is based on function, interaction, structure (FIS) modelling framework that enables modelling complex system and its failures. The resulting model is converted into an executable simulation model based on a new class of Petri Nets (PNs) called predicate-transition, prioritised, synchronous (PTPS) PN. The obtained simulation model is then executed in order to obtain performance indicators in degraded mode. This tool is used during the system design, in order to study the impact of risks on the designed production system performance. It is also used to study an existing production system in order to analyse and optimise its behaviour in degraded mode. In this article, we present our tool and apply it to a special case of production systems which is a hospital sterilisation system.     

Global sensitivity analysis and aggregation of risk in multi-product supply chain networks

Manufacturing firms manage complex supply chain networks which are exposed to a plethora of hazard events. An essential part of the risk management process is the calculation of the stand-alone risk exposures of the product-specific supply chains, but also of the entire multi-product system. In this paper, first, a global sensitivity analysis of the statistical supply chain risk model is conducted. This method helps the decision-makers to understand the risk of the model they are using. Second, a methodology for risk aggregation in multi-product supply chain networks is proposed. The real-world data is used to analyse and validate the model. Supply chain managers equipped with the proposed method will better cope with the risk in supply chains for different product configurations.     

Towards the derivation of an integrated process cost-modelling technique for complex manufacturing systems

Cost modelling is used to support business decisions, especially, when the objective is to remain competitive on price and be able to realise outputs at low cost. Many researchers and industrialists have proposed and experimented with different cost-modelling techniques with a view to influencing design and production decisions at an early stage of the development process. This has led to cost-modelling methods which have been broadly classified in this paper as qualitative and quantitative. The paper identifies current best practice cost-modelling techniques and their performance in complex and dynamic manufacturing environments. The review served as a platform to support the recommendation for an integrated cost-modelling methodology. The integrated methodology is based on the strengths of cost engineering, enterprise modelling, system dynamics and discrete event simulation modelling techniques. The method can help in the redesign and re-engineering of products and processes for better cost and value indications; support investment decision analysis; help determine appropriate business and manufacturing paradigms; influence ‘make, buy or outsourcing’ decisions and serve as a key process improvement tool.     

Using integrated fuzzy DEMATEL and fuzzy C: means algorithm for supplier evaluation and selection

Decision-making techniques are used to help evaluate the current suppliers’ aim at classifying performance of individual suppliers against desired levels of performance, so as to design suitable plans to increase the performance and capabilities of suppliers. In this study, an integrated model is introduced and proposed for increasing the supplier selection and evaluation quality. The methodology is composed of two steps. The first stage is fuzzy decision-making trial and evaluation laboratory method in which the interactions between the evaluation criteria and the criteria weight have been computed. At the second stage, performances of suppliers are assessed using both the criteria weights obtained at the first stage and fuzzy c-means clustering algorithm by classifying the vendors according to their performances. Obtained results show that the proposed model is very well suited as a decision-making tool for supplier selection decisions.     

A simulation based continuous improvement approach for manufacturing based field repair service contracting

This paper develops and tests a novel extension to traditional supplier selection practice, with a particular focus on the concluding stages of a manufacturing-based field service. Action-based research was used to design and develop a discrete event simulation decision support for a large multinational manufacturing organisation with a significant after-sales service supply chain. The framework has been designed to identify and validate the value attributable to collaborative supplier contracting with built-in costed performance improvement targets. Use of the framework in the case organisation was found to produce greater cost savings over traditional practice, facilitating extended supply chain contracts. The results provide evidence of the high level of savings achievable while also improving customer delivery through targeted service improvements over the contracts life cycle. This framework advances beyond the prevalent practice of cost-focused short-term adversarial supply contracting and is innovative in terms of its continuous improvement simulation based framework design.     

地下工程风险评估准则分析与研究

结合地下工程的特点,建设性地提出了地下工程风险评估准则,其成果成功地应用于北京市城市地下道路系统规划设计的研究中.     

Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation

Abstract

As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necessity of controlling the potential risks. Hence, it is indispensable for the industry to establish an effective risk assessment system of supply chain. In this study, an AHP-fuzzy comprehensive evaluation model was developed based on the analytic hierarchy process and fuzzy mathematical theory, which quantitatively assessed the risks of supply chain. Taking polysorbate 80 as the example for model analysis, it was concluded that polysorbate 80 for injection use is a high-risk ingredient in the supply chain compared to that for oral use to achieve safety application in clinic, thus measures should be taken to control and minimize those risks.     

A new heuristic for integrated process planning and scheduling in reconfigurable manufacturing systems

Integrated process planning and scheduling (IPPS) is a manufacturing strategy that considers process planning and scheduling as an integrated function rather than two separated functions performed sequentially. In this paper, we propose a new heuristic to IPPS problem for reconfigurable manufacturing systems (RMS). An RMS consists mainly of reconfigurable machine tools (RMTs), each with multiple configurations, and can perform different operations with different capacities. The proposed heuristic takes into account the multi-configuration nature of machines to integrate both process planning and scheduling. To illustrate the applicability and the efficiency of the proposed heuristic, a numerical example is presented where the heuristic is compared to a classical sequential process planning and scheduling strategy using a discrete-event simulation framework. The results show an advantage of the proposed heuristic over the sequential process planning and scheduling strategy.     

Data quality and uncertainty assessment methodology for pavement LCA

In performing pavement life cycle assessment (LCA), users are facing various reports of energy intensity coefficient (EIC) of pavement materials which differ considerably among data sources and therefore alter the LCA results significantly. Instead of selecting a certain EIC without or of little explanation for the current pavement LCA practices, this study proposed a methodology to build probability density function (PDF) for EIC based on available data-set and their qualities. Each data was first evaluated about the data quality indicator (DQI) through data quality pedigree matrix and converted to PDF in modified Beta distribution form. Three weighting methods, the DQI one, coefficient of variation (COV) one and analytical hierarchy process (AHP) one, were developed to assign weightings for different data. Monte Carlo simulation was run with the weighted PDF of each data as input to obtain the ultimate PDF for EIC. A case study to estimate the bitumen’s EIC with eight data samples were performed using the proposed methodology. It is found (1): the estimates by the proposed methodology is of higher reliability (lower COV) compared to any single data due to utilisation of information of the overall data samples; (2) the AHP weighting method is most favoured despite the results of the three weighting methods are close; (3) the central estimates of bitumen’s EIC are between5.4~5.8 MJ/kg. The proposed methodology is helpful in aiding calculating EICs for pavement materials and capturing uncertainties in LCA results in a statistical sense.     

Fuzzy FMEA in risk assessment for test and calibration laboratories

In this study, it is aimed to compare traditional and fuzzy FMEA in identifying areas that may pose risks and need improvement in Test and Calibration Laboratories. Within this scope, FMEA is used in ranking the possible risks. One hundred ninety-nine failures are detected in 91 inspections, carried out in the Test and Calibration Laboratories. Since FMEA uses experts’ evaluations, which are considered subjective, fuzzy logic is implemented to the approach where the evaluations are presented with linguistic variables. The comparison of FMEA and fuzzy FMEA showed that there exists a high correlation between these two analyses and the order of priority based on the Fuzzy Risk Priority Number calculation is overlapping with the Risk Priority Number sequence. Fuzzy FMEA can also be considered when the evaluations are not trustworthy or incomplete. Therefore, this study can be addressed as an example of how fuzzy implementation to FMEA substantially be used instead of traditional FMEA when there exist qualitative, subjective or incomplete evaluations, or in cases where traditional FMEA has troubles in practice.     

A simulation-enhanced value stream mapping approach for optimisation of complex production environments

Value stream mapping (VSM) is a widely adopted method for transformation of production environments into a lean operational state. The straightforwardness as well as the completeness, with which processes are analysed and optimised, are key to the success of the method originating from the automotive industry. However, these attributes of the ‘paper and pencil’ approach result in limitations when applying VSM in complex production environments. This research paper targets to overcome these limitations, specifically in production environments involving significant demand variability, complex routing and cost factors which potentially increase with lean implementation. For this purpose, an enhanced VSM method is developed, which utilises discrete event simulation (DES). The method features a feasibility and trade-off analysis which is incorporated into the VSM procedure. A case study covering a process of exhaust gas purification catalyst production is then conducted to test the newly developed method. The VSM project yields a shop floor lead time reduction from 11.4 to 1.4?d. The additional DES feasibility and trade-off analysis determines customer demand fulfilment and quantifies the monetary benefit of the future state. In that way, potential iterative implementation which is inherently oppositional to the lean philosophy is avoided.     

An interval probability-based FMEA model for risk assessment: A real-world case

Failure mode and effect analysis (FMEA) is an effective quality tool to eliminate the risks and enhance the stability and safety in the fields of manufacturing and service industry. Nevertheless, the conventional FMEA has been criticized for its drawbacks in the evaluation process of risk factors or the determination of risk priority number (RPN), which may lead to inaccurate evaluation results. Therefore, in this paper, we develop a novel FMEA method based on rough set and interval probability theories. The rough set theory is adopted to manipulate the subjectivity and uncertainty of experts' assessment and convert the evaluation values of risk factors into interval numbers. Meanwhile, the interval exponential RPN (ERPN) is used to replace the traditional RPN due to its superior properties, eg, solving the problems of duplicate numbers and discontinuity of RPN values. Furthermore, an interval probability comparison method is proposed to rank the risk priority of each failure mode for avoiding the information loss in the calculation process of RPN. Finally, a real case study is presented, and the comparison analysis among different FMEA methods is conducted to demonstrate the reliability and effectiveness of the proposed FMEA method.     

盐岩能源地下储备库群风险综合评价与管理体系

利用盐岩洞穴进行能源地下储备是我国能源储备的重点战略部署方向。我国盐岩地层埋深浅,呈层状分布,且夹层较多,地质条件相对复杂,增加储库灾变的可能性,因此建立一套盐岩能源地下储备库群风险综合评价和管理体系尤显重要。根据盐岩地下储库群灾变事故的统计结果,获取了盐岩地下储库的主要风险因子,对库群风险进行了辨识。建立了盐岩地下库群风险评价方法和风险分级标准,通过数值模拟方法对失效概率进行了核算,评价了金坛盐岩库群风险等级,并通过模型试验对结果进行了验证,开发了基于计算机网络技术的盐岩地下库群风险信息管理与评估系统,建立了盐岩能源地下储备库群风险综合评价和管理体系。     

Modelling robustness for manufacturing processes: a critical review

‘Robustness’ is an important concept used in quality engineering for the improvement of quality in a manufacturing process. A process which is insensitive to noise variation is called a robust process. The robustness is modelled by several researchers and practioners for its design and implementation in a manufacturing process. A review of all these approaches is essential in order to assess their strengths, limitations and applicability under different process conditions and constraints. Over the years, many of these approaches have found widespread application in measuring, assessing and modelling of process robustness in manufacturing and other industries. In this paper, an attempt has been made to review critically the existing approaches as proposed and applied for measuring and evaluating robustness of manufacturing processes. Based on the critical appraisal, the key issues are identified and a generic framework for modelling and measuring of process robustness in single- and multi-stage manufacturing processes is presented.     

Combining the cost of reducing uncertainty with the selection of risk assessment models for remediation decision of site contamination

The decision as to whether a contaminated site poses a threat to human health and should be cleaned up relies increasingly upon the use of risk assessment models. However, the more sophisticated risk assessment models become, the greater the concern with the uncertainty in, and thus the credibility of, risk assessment. In particular, when there are several equally plausible models, decision makers are confused by model uncertainty and perplexed as to which model should be chosen for making decisions objectively. When the correctness of different models is not easily judged after objective analysis has been conducted, the cost incurred during the processes of risk assessment has to be considered in order to make an efficient decision. In order to support an efficient and objective remediation decision, this study develops a methodology to cost the least required reduction of uncertainty and to use the cost measure in the selection of candidate models. The focus is on identifying the efforts involved in reducing the input uncertainty to the point at which the uncertainty would not hinder the decision in each equally plausible model. First, this methodology combines a nested Monte Carlo simulation, rank correlation coefficients, and explicit decision criteria to identify key uncertain inputs that would influence the decision in order to reduce input uncertainty. This methodology then calculates the cost of required reduction of input uncertainty in each model by convergence ratio, which measures the needed convergence level of each key input's spread. Finally, the most appropriate model can be selected based on the convergence ratio and cost. A case of a contaminated site is used to demonstrate the methodology.