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.

Model structure and uncertainty for stochastic non-point source modelling applications

The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

Manufacturing vision and competitiveness

Discusses a refinement to the process by which manufacturing strategy is created. Builds on an existing strategy process (Platts, 1990) and adapts it to fit more closely within the dynamic manufacturing vision. The method for creating a manufacturing vision allows a business to do this in a two- to three-week period as part of a 10-12 week manufacturing strategy project. A conceptual model of manufacturing vision has been developed that enables practitioners to explore the factors that influenced the potential competitive contribution of manufacturing and to agree an explicit direction for change. Describes the successful application of the process in six manufacturing organizations and highlights the practical limitations of the approach.

The dynamics of industrial emergence

The need to stimulate, identify and nurture new industries is a prominent challenge in advanced economies. While basic science represents a valuable source of new ideas and opportunities, it can often take decades before this science finally finds application in the market. While numerous studies have to date focused on aspects of industrial evolution, (e.g. innovation, internationalisation, new product introduction, technological lifecycles and emerging technologies), far fewer have focused on technology-based industrial emergence. It is clear that if assistance is to be provided to firms and industrial policymakers attempting to navigate industrial emergence then we need an improved understanding of the characteristics and dynamics of this phenomenon. Accordingly, this paper reviews published work from a range of disparate disciplines - evolutionary theory, social construction of technology (SCOT), complexity science, industrial dynamics and technology management - to identify these dynamics. Through this review we conceptualise industrial emergence as a co-evolutionary process in which nonlinear dynamics operate. Industrial emergence is sensitive to the initial availability of resources and the market applications, with growth dependent on the supply-demand coupling, agents' actions to reduce uncertainty and catalytic events. Through synthesizing these key dynamics we go on to propose a conceptual model for industrial emergence. © 2010 IEEE.

Ecodesign innovation: Is 'early' always 'best'?

This paper explores ecodesign within the product development process (PDP), particularly focusing on the design stages. Previous research has highlighted the early stages as the 'best' place to integrate environmental issues. Here the early stage hypothesis is explored from the perspective of the industrial design department - the early stage designers. Being located at the earliest possible design stages of product development would mean that, were the hypothesis to hold true, industrial design would be the 'best' place to locate ecodesign. Empirical research was conducted with the Industrial Design Centre (IDC) of a global Electrical and Electronic goods manufacture. It used a qualitative, inductive research methodology, based on two 'live' design concept projects, participant observation within the department, and on several semi-structured interviews. Throughout this paper, the empirical work is compared and contrasted to ecodesign literature, specifically to models of ecodesign innovation and the product development process. Beginning by exploring of the early stage hypothesis, the paper concludes with a conceptual model of early stage ecodesign for the context in question.

Factor analysis and structural equation modelling of sustainable behaviour in contaminated land remediation

Contaminated land remediation has traditionally been viewed as sustainable practice because it reduces urban sprawl and mitigates risks to human being and the environment. However, in an emerging green and sustainable remediation (GSR) movement, remediation practitioners have increasingly recognized that remediation operations have their own environmental footprint. The GSR calls for sustainable behaviour in the remediation industry, for which a series of white papers and guidance documents have been published by various government agencies and professional organizations. However, the relationship between the adoption of such sustainable behaviour and its underlying driving forces has not been studied. This study aims to contribute to sustainability science by rendering a better understanding of what drives organizational behaviour in adopting sustainable practices. Factor analysis (FA) and structural equation modelling (SEM) were used to investigate the relationship between sustainable practices and key factors driving these behaviour changes in the remediation field. A conceptual model on sustainability in the environmental remediation industry was developed on the basis of stakeholder and institutional theories. The FA classified sustainability considerations, institutional promoting and impeding forces, and stakeholder's influence. Subsequently the SEM showed that institutional promoting forces had significant positive effects on adopting sustainability measures, and institutional impeding forces had significant negative effects. Stakeholder influences were found to have only marginal direct effect on the adoption of sustainability; however, they exert significant influence on institutional promoting forces, thus rendering high total effect (i.e. direct effect plus indirect effect) on the adoption of sustainability. This study suggests that sustainable remediation represents an advanced sustainable practice, which may only be fully endorsed by both internal and external stakeholders after its regulatory, normative and cognitive components are institutionalized. © 2014 Elsevier Ltd. All rights reserved.

Resonance based multi-gaited robot locomotion

In order to understand the underlying mechanisms of animals' agility, dexterity and efficiency in motor control, there has been an increasing interest in the study of gait patterns in biological and artificial legged systems. This paper presents a novel approach to the study of gait patterns which makes use of intrinsic mechanical dynamics of robotic systems. Each of these robots consists of a U-shape elastic beam and exploits free vibration to generate different gait patterns. We developed a conceptual model for these robots, and through simulation and real-world experiments, we show three distinct mechanisms for generating four different gait patterns in these robots. © 2012 IEEE.