A systems methodology for analysing and simulating manufacturing systems

The Systems Engineering Group (SEG) at De Montfort University are developing the Boardman Soft Systems Methodology (BSSM) which allows complex human systems to be modelled, this work builds upon Checkland's Soft Systems Methodology (1981). The BSSM has been applied to the modelling of the systems engineering process as used in design and manufacturing companies. The BSSM is used to solicit information from a company and this data is then transformed into systemic diagrams (systemigrams). These systemigrams are posited to be accurate and concise representations of the system which has been modelled. This paper describes the collaboration between SEG and a manufacturing company (MC) in Leicester, England. The purpose of this collaboration was twofold. First, it was to create an objective view of the MC's processes, in the form of systemigrams. It was important to get this modelled by a source outside of the company, as it is difficult for people within a system being modelled to be unbiased. Secondly, it allowed a series of systemigrams to be produced which can then be subjected to simulation, for the purpose of aiding risk management decisions and to reduce the project cycle time

A systemic approach to the design of cellular manufacturing systems

Cellular manufacturing is widely acknowledged as one of the key approaches to achieving world-class performance in batch manufacturing operations. The design of cellular manufacturing systems (CMS) is therefore crucial in determining a company's competitiveness. This thesis postulated that, in order to be effective the design of CMS should not only be systematic but also systemic. A systemic design uses the concepts of the body of work known as the 'systems approach' to ensure that a truly effective CMS is defined. The thesis examined the systems approach and created a systemic framework against which existing approaches to the design of CMS were evaluated. The most promising of these, Manufacturing Systems Engineering (MSE), was further investigated using a series of cross-sectional case-studies. Although, in practice, MSE proved to be less than systemic, it appeared to produce significant benefits. This seemed to suggest that CMS design did not need to be systemic to be effective. However, further longitudinal case-studies showed that the benefits claimed were at an operational level not at a business level and also that the performance of the whole system had not been evaluated. The deficiencies identified in the existing approaches to designing CMS were then addressed by the development of a novel CMS design methodology that fully utilised systems concepts. A key aspect of the methodology was the use of the Whole Business Simulator (WBS), a modelling and simulation tool that enabled the evaluation of CMS at operational and business levels. The most contentious aspects of the methodology were tested on a significant and complex case-study. The results of the exercise indicated that the systemic methodology was feasible.

Using a systems approach in logistics design and planning

The international economic and business environment continues to develop at a rapid rate. Increasing interactions between economies, particularly between Europe and Asia, has raised many important issues regarding transport infrastructure, logistics and broader supply chain management. The potential exists to further stimulate trade provided that these issues are addressed in a logical and systematic manner. However, if this potential is to be realised in practice there is a need to re-evaluate current supply chain configurations. A mismatch currently exists between the technological capability and the supply chain or logistical reality. This mismatch has sharpened the focus on the need for robust approaches to supply chain re-engineering. Traditional approaches to business re-engineering have been based on manufacturing systems engineering and business process management. A recognition that all companies exist as part of bigger supply chains has fundamentally changed the focus of re-engineering. Inefficiencies anywhere in a supply chain result in the chain as a whole being unable to reach its true competitive potential. This reality, combined with the potentially radical impact on business and supply chain architectures of the technologies associated with electronic business, requires organisations to adopt innovative approaches to supply chain analysis and re-design. This paper introduces a systems approach to supply chain re-engineering which is aimed at addressing the challenges which the evolving business environment brings with it. The approach, which is based on work with a variety of both conventional and electronic supply chains, comprises underpinning principles, a methodology and guidelines on good working practice, as well as a suite of tools and techniques. The adoption of approaches such as that outlined in this paper helps to ensure that robust supply chains are designed and implemented in practice. This facilitates an integrated approach, with involvement of all key stakeholders throughout the design process.

Large-scale complex IT systems

Society depends on complex IT systems created by integrating and orchestrating independently managed systems. The incredible increase in scale and complexity in them over the past decade means new software-engineering techniques are needed to help us cope with their inherent complexity. The key characteristic of these systems is that they are assembled from other systems that are independently controlled and managed. While there is increasing awareness in the software engineering community of related issues, the most relevant background work comes from systems engineering. The interacting algos that led to the Flash Crash represent an example of a coalition of systems, serving the purposes of their owners and cooperating only because they have to. The owners of the individual systems were competing finance companies that were often mutually hostile. Each system jealously guarded its own information and could change without consulting any other system.

Efficiency measurement in fuzzy additive data envelopment analysis

Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers' intuition and subjective judgements. This paper extends the conventional DEA models to a fuzzy framework by proposing a new fuzzy additive DEA model for evaluating the efficiency of a set of decision-making units (DMUs) with fuzzy inputs and outputs. The contribution of this paper is threefold: (1) we consider ambiguous, uncertain and imprecise input and output data in DEA, (2) we propose a new fuzzy additive DEA model derived from the a-level approach and (3) we demonstrate the practical aspects of our model with two numerical examples and show its comparability with five different fuzzy DEA methods in the literature. Copyright © 2011 Inderscience Enterprises Ltd.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Understanding enterprise behaviour:a feasibility study

This paper describes work conducted as a joint collaboration between the Virtual Design Team (VDT) research group at Stanford University (USA) , the Systems Engineering Group (SEG) at De Montfort University (UK) and Elipsis Ltd . We describe a new docking methodology in which we combine the use of two radically different types of organizational simulation tool. The VDT simulation tool operates on a standalone computer, and employs computational agents during simulated execution of a pre-defined process model (Kunz, 1998). The other software tool, DREAMS , operates over a standard TCP/IP network, and employs human agents (real people) during a simulated execution of a pre-defined process model (Clegg, 2000).

Software engineering techniques for the development of systems of systems

This paper investigates how existing software engineering techniques can be employed, adapted and integrated for the development of systems of systems. Starting from existing system-of-systems (SoS) studies, we identify computing paradigms and techniques that have the potential to help address the challenges associated with SoS development, and propose an SoS development framework that combines these techniques in a novel way. This framework addresses the development of a class of IT systems of systems characterised by high variability in the types of interactions between their component systems, and by relatively small numbers of such interactions. We describe how the framework supports the dynamic, automated generation of the system interfaces required to achieve these interactions, and present a case study illustrating the development of a data-centre SoS using the new framework.

The application of knowledge based expert systems to mechanical engineering design

Investigation of the different approaches used by Expert Systems researchers to solve problems in the domain of Mechanical Design and Expert Systems was carried out. The techniques used for conventional formal logic programming were compared with those used when applying Expert Systems concepts. A literature survey of design processes was also conducted with a view to adopting a suitable model of the design process. A model, comprising a variation on two established ones, was developed and applied to a problem within what are described as class 3 design tasks. The research explored the application of these concepts to Mechanical Engineering Design problems and their implementation on a microcomputer using an Expert System building tool. It was necessary to explore the use of Expert Systems in this manner so as to bridge the gap between their use as a control structure and for detailed analytical design. The former application is well researched into and this thesis discusses the latter. Some Expert System building tools available to the author at the beginning of his work were evaluated specifically for their suitability for Mechanical Engineering design problems. Microsynics was found to be the most suitable on which to implement a design problem because of its simple but powerful Semantic Net Knowledge Representation structure and the ability to use other types of representation schemes. Two major implementations were carried out. The first involved a design program for a Helical compression spring and the second a gearpair system design. Two concepts were proposed in the thesis for the modelling and implementation of design systems involving many equations. The method proposed enables equation manipulation and analysis using a combination of frames, semantic nets and production rules. The use of semantic nets for purposes other than for psychology and natural language interpretation, is quite new and represents one of the major contributions to knowledge by the author. The development of a purpose built shell program for this type of design problems was recommended as an extension of the research. Microsynics may usefully be used as a platform for this development.

Systems development of data retrieval for an engineering company's after-sales service

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Knowledge-based systems and engineering software

The work described was carried out as part of a collaborative Alvey software engineering project (project number SE057). The project collaborators were the Inter-Disciplinary Higher Degrees Scheme of the University of Aston in Birmingham, BIS Applied Systems Ltd. (BIS) and the British Steel Corporation. The aim of the project was to investigate the potential application of knowledge-based systems (KBSs) to the design of commercial data processing (DP) systems. The work was primarily concerned with BIS's Structured Systems Design (SSD) methodology for DP systems development and how users of this methodology could be supported using KBS tools. The problems encountered by users of SSD are discussed and potential forms of computer-based support for inexpert designers are identified. The architecture for a support environment for SSD is proposed based on the integration of KBS and non-KBS tools for individual design tasks within SSD - The Intellipse system. The Intellipse system has two modes of operation - Advisor and Designer. The design, implementation and user-evaluation of Advisor are discussed. The results of a Designer feasibility study, the aim of which was to analyse major design tasks in SSD to assess their suitability for KBS support, are reported. The potential role of KBS tools in the domain of database design is discussed. The project involved extensive knowledge engineering sessions with expert DP systems designers. Some practical lessons in relation to KBS development are derived from this experience. The nature of the expertise possessed by expert designers is discussed. The need for operational KBSs to be built to the same standards as other commercial and industrial software is identified. A comparison between current KBS and conventional DP systems development is made. On the basis of this analysis, a structured development method for KBSs in proposed - the POLITE model. Some initial results of applying this method to KBS development are discussed. Several areas for further research and development are identified.

Engineering liposomal systems to develop solubility enhancing technology

This research primarily focused on identifying the formulation parameters which control the efficacy of liposomes as delivery systems to enhance the delivery of poorly soluble drugs. Preliminary studies focused on the drug loading of ibuprofen within vesicle systems. Initially both liposomal and niosomal formulations were screened for their drug-loading capacity: liposomal systems were shown to offer significantly higher ibuprofen loading and thereafter lipid based systems were further investigated. Given the key role cholesterol is known to play within the stability of bilayer vesicles. the optimum cholesterol content in terms of drug loading and release of poorly soluble drugs was then investigated. From these studies a concentration of 11 total molar % of cholesterol was used as a benchmark for all further formulations. Investigating the effect of liposomc composition on several low solubility drugs, drug loading was shown to be enhanced by adopting longer chain length lipids. cationic lipids and. decreasing drug molecular weight. Drug release was increased by using cationic lipids and lower molecular weight of drug; conversely, a reduction was noted when employing longer chain lipids thus supporting the rational of longer chain lipids producing more stable liposomes, a theory also supported by results obtained via Langmuir studies· although it was revealed that stability is also dependent on geometric features associated with the lipid chain moiety. Interestingly, reduction in drug loading appeared to be induced when symmetrical phospholipids were substituted for lipids constituting asymmetrical alkyl chain groups thus further highlighting the importance of lipid geometry. Combining a symmetrical lipid with an asymmetrical derivative enhanced encapsulation of a hydrophobic drug while reducing that of another suggesting the importance of drug characteristics. Phosphatidylcholine liposornes could successfully be prepared (and visualised using transmission electron microscopy) from fatty alcohols therefore offering an alternative liposomal stabiliser to cholesterol. Results obtained revealed that liposomes containing tetradecanol within their formulation shares similar vesicle size, drug encapsulation, surface charge. and toxicity profiles as liposomes formulated with cholesterol, however the tetradecanol preparation appeared to release considerably more drug during stability studies. Langmuir monolayer studies revealed that the condensing influence by tetradecanol is less than compared with cholesterol suggesting that this reduced intercalation by the former could explain why the tetradecanol formulation released more drug compared with cholesterol formulations. Environmental scanning electron microscopy (ESEM) was used to analyse the morphology and stability of liposomes. These investigations indicated that the presence of drugs within the liposomal bilayer were able to enhance the stability of the bilayers against collapse under reduced hydration conditions. In addition the presence of charged lipids within the formulation under reduced hydration conditions compared with its neutral counterpart. However the applicability of using ESEM as a new method to investigate liposome stability appears less valid than first hoped since the results are often open to varied interpretation and do not provide a robust set of data to support conclusions in some cases.