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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.

Sustainable manufacturing appears to be a rapidly developing field and it would be expected that there is a growing body of knowledge in this area. Initial examination of the literature shows evidence of sustainable work in the areas of product design, supply chain, production technology and waste avoidance activities. Manufacturers publish metrics showing significant improvements in environmental performance at high level but information on how these improvements are achieved is sparse. Examining peer reviewed publications focused on production operations there are few cases reporting details and there has been little prior analysis of published sustainable manufacturing activity. Moreover, the mismatch between academic and practitioner language leads to challenges in interpretation. This paper captures and analyses the types of sustainable manufacturing activities through literature review. In turn this can help manufacturers to access examples of good practice and help academics identify areas for future research.

The rapid development and implementation of digitalization in manufacturing has enormous impact on the environment. It is still unclear whether digitalization has positive or negative environmental impact from applications in manufacturing. Therefore, this study aims to discuss the overall implications of digitalization on environmental sustainability through a literature study, within the scope of manufacturing (product design, production, transportation, and customer service). The analysis and categorization of selected articles resulted in two main findings: (1) Digitalization in manufacturing contributes positively to environmental sustainability by increasing resource and information efficiency as a result of applying Industry 4.0 technologies throughout the product lifecycle; (2) the negative environmental burden of digitalization is primarily due to increased resource and energy use, as well as waste and emissions from manufacturing, use, and disposal of the hardware (the technology lifecycle). Based on these findings, a lifecycle perspective is proposed, considering the environmental impacts from both the product and technology lifecycles. This study identified key implications of digitalization on environmental sustainability in manufacturing to increase awareness of both the positive and negative impacts of digitalization and thereby support decision making to invest in new digital technologies.