Remanufacturing is recognized as a major circular economy option to recover and upgrade functions from post-use products. However, the inefficiencies associated with operations, mainly due to the uncertainty and variability of material flows and product conditions, undermine the growth of remanufacturing. With the objective of supporting the design and management of more proficient and robust remanufacturing processes, this paper proposes a generic and reconfigurable simulation model of remanufacturing systems. The developed model relies upon a modular framework that enables the user to handle multiple process settings and production control policies, among which token-based policies. Customizable to the characteristics of the process under analysis, this model can support logistics performance evaluation of different production control policies, thus enabling the selection of the optimal policy in specific business contexts. The proposed model is applied to a real remanufacturing environment in order to validate and demonstrate its applicability and benefits in the industrial settings.
Driven by public awareness and international regulations and standards, sustainability and environmental impacts have become increasingly important distinguishing factors between competing products and services. Circular economy aims to increase economic growth by using natural resources and ecosystems in a more effective way with the aim of maintaining products, components and materials at their highest utility and value at all times. More effective use of materials enables the creation of more value both by cost savings and by developing new markets or by developing existing ones. Reduced acquisition of resources is a driver for innovation for sustainable use of materials, components and products as well as new business models. This chapter introduces methods and tools to assess and reduce environmental impacts, and improve resource efficiency and sustainability management. Life cycle thinking forms one of the basic principles of sustainable development, and Life Cycle Assessment (LCA) is the leading method for assessing the potential environmental impacts of a product, process or service throughout its life cycle (ISO 14040-44). Other methods based on life cycle thinking are also introduced. LCA focusing on the contribution of a product or service to global warming uses methods for Carbon Footprint measurement and facilitates the tracking of greenhouse gas (GHG) emissions (ISO 14067). Water footprint is a tool that assesses the magnitude of potential water-specific environmental impacts of water use associated with a product, process or organisation. It aims at describing the impact of water utilization on humans and ecosystems due to changes in water quality and quantity (ISO 14046 Environmental managementWater footprint-Principles, requirements and guidelines 2014). The concept of handprint has recently been introduced to measure and communicate the positive changes of actions and the beneficial impacts created within the life cycle of products, services, processes, companies, organizations or individuals. A handprint of a product can be created either by preventing or avoiding negative impacts (footprints), or by creating positive benefits. When adopting the circular economy way of thinking, companies need these tools and methods to ensure resource efficiency, cost cuts and improvements in their environmental performance which provide them with more earning opportunities. Fundamental changes throughout the value chain, from product design and production processes to new business models and consumption patterns, support this trend.
Purpose This paper studies the carbon footprint and water scarcity footprint (WSF) of a milk protein, beta-lactoglobulin, produced by cellular agriculture and compares this to extracted dairy protein from milk. The calculations of the microbially produced proteins were based on a model of a hypothetical industrial-scale facility. The purpose of the study is to examine the role relative to dairy of microbially produced milk proteins in meeting future demand for more sustainably produced protein of high nutritional quality. Methods The evaluated process considers beta-lactoglobulin production in bioreactor cultivation with filamentous fungi T. reesei and downstream processing for product purification. The model considers four production scenarios in four different locations (New Zealand, Germany, US, and Australia) with a cradle-to-gate system boundary. The scenarios consider different sources of carbon (glucose and sucrose), different options for the fungal biomass treatment (waste or animal feed) and for the purification of the product. Allocation to biomass was avoided by considering it substituting the production of general protein feed. The carbon footprint and WSF (based on AWaRe factors) modelling is compared to calculations and actual data on extracted dairy protein production in NZ. The uncertainties of modelled process were addressed with a sensitivity analysis. Results and discussion The carbon footprint of microbially produced protein varied depending on the location (energy profile) and source of carbon used. The lowest carbon footprint (5.5 t CO2e/t protein) was found with sucrose-based production in NZ and the highest (17.6 t CO2e/t protein) in Australia with the glucose and chromatography step. The WSF results varied between 88–5030 m3 world eq./t protein, depending on the location, type of sugar and purification method used. The avoided feed production had a bigger impact on the WSF than on the carbon footprint. Both footprints were sensitive to process parameters of final titre and protein yield from sugar. The results for milk protein were of similar magnitude, c.10 t CO2e/t protein and 290–11,300 m3 world eq./t protein. Conclusions The environmental impacts of microbially produced milk protein were of the same magnitude as for extracted dairy protein. The main contributions were sugar and electricity production. The carbon footprints of proteins produced by cellular agriculture have potential for significant reduction when renewable energy and more sustainable carbon sources are used and combined with evolving knowledge and technology in microbial production. Similarly, the carbon footprint of milk proteins can potentially be reduced through methane reduction technologies.
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