Deriving a systematic approach to changeable manufacturing system design

It has long been argued that Factories are long life and complex products. The complexity of designing factories, and their underlying manufacturing systems, is further amplified when dealing with continuously changing customer demands. At the same time, due to research fragmentation, little if any scientific explanations are available supporting and exploiting the paradigm that "factories are products". In order to address this weakness, this paper presents research results arising from a comparative analysis of systematic "product design" and "manufacturing system design" approaches. The contribution emerging from this research is an integrated systematic design approach to changeable manufacturing systems, based on scientific concepts founded upon product design theories, and is explained through a case study in the paper. This research is part of collaboration between the CERU University of Malta and IAO Fraunhofer aimed at developing a digital decision support tool for planning changeable manufacturing systems.peer-reviewe

Interaction with rule-bound systems : introducing a new 'ideal type' problem context

This PhD thesis introduces a new ideal-type problem context of rule-bound systems. The thesis has been generated through a belief in the ability of metaphor to make the abstract visible, its capacity to make the unfamiliar familiar, and its effectiveness as a legitimate means of generating insight and organizing knowledge. Metaphorical description remains an integral part of this thesis from beginning to end.It shows how the new context of rule-bound systems provides closure of the ideal problem context grid along the participants access. Following the ideas that created the basis for this closure, insight into a new role for systems practitioners is provided and the ideal problem context grid developed to form of a Torus.Part 1 outlines the theoretical foundations and other inspirations that underpin the thesis. Grounded on a wider definition of rules, including rules in both a formal and informal sense, multiple ways of viewing rules are highlighted. The characteristics of rule-bound systems are identified, drawing comparisons with other 'ideal-types'. Suggestions are also drawn out as to how change might be affected in a rule-bound context. Part II of this thesis is an account of a real world intervention informed by Critical Systems Thinking, carried out under the auspices of Participatory Action Research. A number of systems research methods and concepts were employed to investigate the participation of students in policy making in two contrasting senior schools in the North of England - organizations believed to present many of the characteristics of the rule-bound system. The approach used was one mixing methods, specifically, the creation of a symbiotic relationship between Soft Systems Methodology and Critical Systems Heuristics. Part III describes the process of reflection undertaken and the conclusion to the thesis

Systems Engineering Leading Indicators Guide, Version 1.0

The Systems Engineering Leading Indicators guide set reflects the initial subset of possible indicators that were considered to be the highest priority for evaluating effectiveness before the fact. A leading indicator is a measure for evaluating the effectiveness of a how a specific activity is applied on a program in a manner that provides information about impacts that are likely to affect the system performance objectives. A leading indicator may be an individual measure, or collection of measures, that are predictive of future system performance before the performance is realized. Leading indicators aid leadership in delivering value to customers and end users, while assisting in taking interventions and actions to avoid rework and wasted effort. The Systems Engineering Leading Indicators Guide was initiated as a result of the June 2004 Air Force/LAI Workshop on Systems Engineering for Robustness, this guide supports systems engineering revitalization. Over several years, a group of industry, government, and academic stakeholders worked to define and validate a set of thirteen indicators for evaluating the effectiveness of systems engineering on a program. Released as version 1.0 in June 2007 the leading indicators provide predictive information to make informed decisions and where necessary, take preventative or corrective action during the program in a proactive manner. While the leading indicators appear similar to existing measures and often use the same base information, the difference lies in how the information is gathered, evaluated, interpreted and used to provide a forward looking perspective

Systems Engineering Leading Indicators Guide, Version 2.0

The Systems Engineering Leading Indicators Guide editorial team is pleased to announce the release of Version 2.0. Version 2.0 supersedes Version 1.0, which was released in July 2007 and was the result of a project initiated by the Lean Advancement Initiative (LAI) at MIT in cooperation with: the International Council on Systems Engineering (INCOSE), Practical Software and Systems Measurement (PSM), and the Systems Engineering Advancement Research Initiative (SEAri) at MIT. A leading indicator is a measure for evaluating the effectiveness of how a specific project activity is likely to affect system performance objectives. A leading indicator may be an individual measure or a collection of measures and associated analysis that is predictive of future systems engineering performance. Systems engineering performance itself could be an indicator of future project execution and system performance. Leading indicators aid leadership in delivering value to customers and end users and help identify interventions and actions to avoid rework and wasted effort. Conventional measures provide status and historical information. Leading indicators use an approach that draws on trend information to allow for predictive analysis. By analyzing trends, predictions can be forecast on the outcomes of certain activities. Trends are analyzed for insight into both the entity being measured and potential impacts to other entities. This provides leaders with the data they need to make informed decisions and where necessary, take preventative or corrective action during the program in a proactive manner. Version 2.0 guide adds five new leading indicators to the previous 13 for a new total of 18 indicators. The guide addresses feedback from users of the previous version of the guide, as well as lessons learned from implementation and industry workshops. The document format has been improved for usability, and several new appendices provide application information and techniques for determining correlations of indicators. Tailoring of the guide for effective use is encouraged. Additional collaborating organizations involved in Version 2.0 include the Naval Air Systems Command (NAVAIR), US Department of Defense Systems Engineering Research Center (SERC), and National Defense Industrial Association (NDIA) Systems Engineering Division (SED). Many leading measurement and systems engineering experts from government, industry, and academia volunteered their time to work on this initiative

Farming Systems Research

Report on the February 1986 Inter Center Workshop on Farming Systems Research (FSR) held at ICRISAT Center, Hyderabad, India. The Workshop, which was suggested by TAC, which noted that 14% of the system's resources was devoted to farming systems in some form. The meeting was intended to help centers develop a unified understanding of how FSR should be approached, to assess the relevance, impact, and priority of such research in the CGIAR, and to outline its future directions. It drew on the stripe review of 1978 on this subject. A statement by representatives of the nine IARCs attending is attached.Agenda document, TAC 39th Meeting, March 1986

Constrained dynamic control of traffic junctions

Excessive traffic in our urban environments has detrimental effects on our health, economy and standard of living. To mitigate this problem, an adaptive traffic lights signalling scheme is developed and tested in this paper. This scheme is based on a state space representation of traffic dynamics, controlled via a dynamic programme. To minimise implementation costs, only one loop detector is assumed at each link. The comparative advantages of the proposed system over optimal fixed time control are highlighted through an example. Results will demonstrate the flexibility of the system when applied to different junctions. Monte Carlo runs of the developed scheme highlight the consistency and repeatability of these results.peer-reviewe