Selecting a multi-agent system development tool for industrial applications: A case study of self-serving aircraft assets

Industrialists have few example processes they can benchmark against in order to choose a multi-agent development kit. In this paper we present a review of commercial and academic agent tools with the aim of selecting one for developing an intelligent, self-serving asset architecture. In doing so, we map and enhance relevant assessment criteria found in literature. After a preliminary review of 20 multiagent platforms, we examine in further detail those of JADE, JACK and Cougaar. Our findings indicate that Cougaar is well suited for our requirements, showing excellent support for criteria such as scalability, persistence, mobility and lightweightness. © 2010 IEEE.

Industrial ecology at factory level - A conceptual model

Growing environmental concerns caused by natural resource depletion and pollution need to be addressed. One approach to these problems is Sustainable Development, a key concept for our society to meet present as well as future needs worldwide. Manufacturing clearly has a major role to play in the move towards a more sustainable society. However it appears that basic principles of environmental sustainability are not systematically applied, with practice tending to focus on local improvements. The aim of the work presented in this paper is to adopt a more holistic view of the factory unit to enable opportunities for wider improvement. This research analyses environmental principles and industrial practice to develop a conceptual manufacturing ecosystem model as a foundation to improve environmental performance. The model developed focuses on material, energy and waste flows to better understand the interactions between manufacturing operations, supporting facilities and surrounding buildings. The research was conducted in three steps: (1) existing concepts and models for industrial sustainability were reviewed and environmental practices in manufacturing were collected and analysed; (2) gaps in knowledge and practice were identified; (3) the outcome is a manufacturing ecosystem model based on industrial ecology (IE). This conceptual model has novelty in detailing IE application at factory level and integrating all resource flows. The work is a base on which to build quantitative modelling tools to seek integrated solutions for lower resource input, higher resource productivity, fewer wastes and emissions, and lower operating cost within the boundary of a factory unit. © 2012 Elsevier Ltd. All rights reserved.

Industrial ecology at factory level: A prototype methodology

The concept of sustainable manufacturing is a form of pollution prevention that integrates environmental considerations in the production of goods while focusing on efficient resource use. Taking the industrial ecology perspective, this efficiency comes from improved resource flow management. The assessment of material, energy and waste resource flows, therefore, offers a route to viewing and analysing a manufacturing system as an ecosystem using industrial ecology biological analogy and can, in turn, support the identification of improvement opportunities in the material, energy and waste flows. This application of industrial ecology at factory level is absent from the literature. This article provides a prototype methodology to apply the concepts of industrial ecology using material, energy and waste process flows to address this gap in the literature. Various modelling techniques were reviewed and candidates selected to test the prototype methodology in an industrial case. The application of the prototype methodology showed the possibility of using the material, energy and waste resource flows through the factory to link manufacturing operations and supporting facilities, and to identify potential improvements in resource use. The outcomes of the work provide a basis to build the specifications for a modelling tool that can support those analysing their manufacturing system to improve their environmental performance and move towards sustainable manufacturing. © IMechE 2012.

Product intelligence in industrial control: Theory and practice

This paper explores the evolving industrial control paradigm of product intelligence. The approach seeks to give a customer greater control over the processing of an order - by integrating technologies which allow for greater tracking of the order and methodologies which allow the customer [via the order] to dynamically influence the way the order is produced, stored or transported. The paper examines developments from four distinct perspectives: conceptual developments, theoretical issues, practical deployment and business opportunities. In each area, existing work is reviewed and open challenges for research are identified. The paper concludes by identifying four key obstacles to be overcome in order to successfully deploy product intelligence in an industrial application. © 2013 Elsevier Ltd. All rights reserved.

Understanding and navigating industrial emergence

Industrial emergence is a broad and complex domain, with relevant perspectives ranging in scale from the individual entrepreneur and firm with the business decisions and actions they make to the policies of nations and global patterns of industrialisation. The research described in this article has adopted a holistic approach, based on structured mapping methods, in an attempt to depict and understand the dynamics and patterns of industrial emergence across a broad spectrum from early scientific discovery to large-scale industrialisation. The breadth of scope and application has enabled a framework and set of four tools to be developed that have wide applicability. The utility of the approaches has been demonstrated through case studies and trials in a diverse range of industrial contexts. The adoption of such a broad scope also presents substantial challenges and limitations, with these providing an opportunity for further research. © IMechE 2013.

An exploration of risk management in global industrial investment

This article explores risk management in global industrial investment by identifying linkages and gaps between theories and practices. It identifies opportunities for further development of the field. Three related bodies of literature have been reviewed: risk management, global manufacturing and investment. The review suggests that risk management in global manufacturing is overlooked in the literature; that existing theoretical risk management processes are not well developed in the global manufacturing context and that the investment literature applies mainly to financial risk assessment rather than investment risk management structures. Further, there appears to be a serious lack of systematic industrial risk management in investment decision making. This article highlights the opportunities to deploy current good practices more effectively as well as the need to develop more robust theories of industrial investment risk management. The approach adopted to investigate this multidisciplinary topic included a historical review of literature to understand the diverse background of theoretical development. A case study research approach was adopted to collect data, involving four global manufacturing companies and one risk management advisory company to observe the patterns and rationale of current practices. Supporting arguments from secondary data sources reinforced the findings. The research focuses risk management in global industrial investment. It links theories with practice to understand the existing knowledge gap and proposes key research themes for further research. © 2013 Macmillan Publishers Ltd. 1460-3799 Risk Management.