A transparent and comparable understanding of the energy efficiency, carbon footprint, and environmental impacts of renewable resources are required in the decision making and planning process towards a more sustainable energy system. Therefore, a new approach is proposed for measuring the environmental sustainability of anaerobic digestion green gas production pathways. The approach is based on the industrial metabolism concept, and is expanded with three known methods. First, the Material Flow Analysis method is used to simulate the decentralized energy system. Second, the Material and Energy Flow Analysis method is used to determine the direct energy and material requirements. Finally, Life Cycle Analysis is used to calculate the indirect material and energy requirements, including the embodied energy of the components and required maintenance. Complexity will be handled through a modular approach, which allows for the simplification of the green gas production pathway while also allowing for easy modification in order to determine the environmental impacts for specific conditions and scenarios. Temporal dynamics will be introduced in the approach through the use of hourly intervals and yearly scenarios. The environmental sustainability of green gas production is expressed in (Process) Energy Returned on Energy Invested, Carbon Footprint, and EcoPoints. The proposed approach within this article can be used for generating and identifying sustainable solutions. By demanding a clear and structured Material and Energy Flow Analysis of the production pathway and clear expression for energy efficiency and environmental sustainability the analysis or model can become more transparent and therefore easier to interpret and compare. Hence, a clear ruler and measuring technique can aid in the decision making and planning process towards a more sustainable energy system.
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In the production of fermented foods, microbes play an important role. Optimization of fermentation processes or starter culture production traditionally was a trial-and-error approach inspired by expert knowledge of the fermentation process. Current developments in high-throughput 'omics' technologies allow developing more rational approaches to improve fermentation processes both from the food functionality as well as from the food safety perspective. Here, the authors thematically review typical bioinformatics techniques and approaches to improve various aspects of the microbial production of fermented food products and food safety.
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Mastering academic language (AL) by elementary school students is important for achieving school success. The extent to which teachers play a role in stimulating students’ AL development may differ. Two types of AL stimulating behavior are distinguished: aimed at students’ understanding and at triggering students’ production of AL. As mathematics requires abstract language use, AL occurs frequently. The instructional methods teachers use during mathematics instruction may offer different opportunities for AL stimulating behavior. In our first study, based on expert opinions, instructional methods were categorized according to opportunities they offer for stimulating students’ AL development. In the second study, video-observations of mathematics instruction of elementary school teachers were analyzed with respect to AL stimulating behavior and instructional methods used. Results showed that actual AL stimulating behavior of teachers corresponds to the expert opinions, except for behavior shown during task evaluation. Teachers differ in time and frequency of their use of instructional methods and therefore in opportunities for stimulating AL development. Four teaching profiles, reflecting different AL stimulating potential, were constructed: ‘teacher talking’, ‘balanced use of methods’, ‘getting students at work’ and ‘interactive teaching’. Teachers showed more types of behavior aimed at students’ AL understanding than at production.
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Sustainable consumption is interlinked with sustainable production. This chapter will introduce the closed-loop production, the circular economy, the steady state economy, and Cradle to Cradle (C2C) models of production. It will reflect on the key blockages to a meaningful sustainable production and how these could be overcome, particularly in the context of business education. The case study of the course for bachelor’s students within International Business Management Studies (IBMS) program at three Universities of Applied Science (vocational schools), and at Leiden University College in The Netherlands will be discussed. Student teams from these schools were given the assignment to make a business plan for a selected sponsor company in order to advise them how to make a transition from a linear to circular economy model. These case studies will illustrate the opportunities as well as potential pitfalls of the closed loop production models. The results of case studies’ analysis show that there was a mismatch between expectations of the sponsor companies and those of students on the one hand and a mismatch between theory and practice on the other hand. The former mismatch is explained by the fact that the sponsor companies have experienced a number of practical constraints when confronted with the need for the radical overhaul of established practices within the entire supply chain and students have rarely considered the financial viability of the "ideal scenarios" of linear-circular transitions. The latter mismatch applies to what students had learned about macro-economic theory and the application through micro-economic scenarios in small companies. https://www.springer.com/gp/book/9783319656076 LinkedIn: https://www.linkedin.com/in/helenkopnina/
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High-tech horticulture production methods (such as vertical farming, hydroponics and other related technology possibilities), combined with evolving market side possibilities (consumer’s willingness to pay for variety, food safety and security), are opening new ways to create and deliver value. In this paper we present four emerging business models and attempt to understand the conditions under which each business model is able to create positive market value and sustained business advantage. The first of these four models is the case of a vertically integrated production to retail operation. The second model is the case of a production model with assured retail/distribution side commitment. The third model deals with a marketing/branding driven production model with differentiated market positioning. Finally, the forth is a production model with direct delivery to the end-consumer based upon the leveraging of wide spread digital technology in the consumer market. To demonstrate these four business models, we analyze practical case studies and analyze their market approach and impact. Using this analysis, we create a framework that enables entrepreneurs and businesses to adopt a business model that matches their capabilities with market opportunities.
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The current set of research methods on ictresearchmethods.nl contains only one research method that refers to machine learning: the “Data analytics” method in the “Lab” strategy. This does not reflect the way of working in ML projects, where Data Analytics is not a method to answer one question but the main goal of the project. For ML projects, the Data Analytics method should be divided in several smaller steps, each becoming a method of its own. In other words, we should treat the Data Analytics (or more appropriate ML engineering) process in the same way the software engineering process is treated in the framework. In the remainder of this post I will briefly discuss each of the existing research methods and how they apply to ML projects. The methods are organized by strategy. In the discussion I will give pointers to relevant tools or literature for ML projects.
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Living labs are complex multi-stakeholder collaborations that often employ a usercentred and design-driven methodology to foster innovation. Conventional management tools fall short in evaluating them. However, some methods and tools dedicated to living labs' special characteristics and goals have already been developed. Most of them are still in their testing phase. Those tools are not easily accessible and can only be found in extensive research reports, which are difficult to dissect. Therefore, this paper reviews seven evaluation methods and tools specially developed for living labs. Each section of this paper is structured in the following manner: tool’s introduction (1), who uses the tool (2), and how it should be used (3). While the first set of tools, namely “ENoLL 20 Indicators”, “SISCODE Self-assessment”, and “SCIROCCO Exchange Tool” assess a living lab as an organisation and are diving deeper into the organisational activities and the complex context, the second set of methods and tools, “FormIT” and “Living Lab Markers”, evaluate living labs’ methodologies: the process they use to come to innovations. The paper's final section presents “CheRRIes Monitoring and Evaluation Tool” and “TALIA Indicator for Benchmarking Service for Regions”, which assess the regional impact made by living labs. As every living lab is different regarding its maturity (as an organisation and in its methodology) and the scope of impact it wants to make, the most crucial decision when evaluating is to determine the focus of the assessment. This overview allows for a first orientation on worked-out methods and on possible indicators to use. It also concludes that the existing tools are quite managerial in their method and aesthetics and calls for designers and social scientists to develop more playful, engaging and (possibly) learning-oriented tools to evaluate living labs in the future. LinkedIn: https://www.linkedin.com/in/overdiek12345/ https://www.linkedin.com/in/mari-genova-17a727196/?originalSubdomain=nl
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Companies in the Brainport region are often characterized as high mix low volume (HMLV) production environments. These companies are distinguished by a wide range of possible products (high product variety), which are produced in low volumes. These are often customer-specific products that are produced once or incidentally. Traditionally, these companies focus on efficient use of resources, where utilisation rate and cost coverage are relevant. The increasing customer demand in the region leads to pressure on production capacity. An initial intuitive response from these companies is to further increase the utilisation rate of machines. To keep costs manageable, the company tries to avoid investing in additional capacity. An undesirable side effect is increasing pressure on timeliness (delivery, such as lead times, delivery reliability, flexibility) and quality. The apparent contradiction between costs and timeliness in these HMLV production environments is a recurring issue in practice-oriented research conducted by Fontys Industrial Engineering and Management students. This results in the following research question: Which sub-aspects may be relevant to the performance regarding Quality, Delivery, and Cost (QDC) of an HMLV production environment?
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Author supplied: The production system described in this paper in an im- plementation of an agile agent-based production system. This system is designed to meet the requirements of modern production, where short time to market, requirement-driven production and low cost small quan- tity production are important issues. The production is done on special devices called equiplets. A grid of these equiplets connected by a fast network is capable of producing a variety of diverent products in parallel. The multi-agent-based software infrastructure is responsible for the agile manufacturing. A product agent is responsible for the production of a single product and equiplet agents will perform the production steps to assemble the product. This paper describes this multiagent-based production system with the focus on the product agent.
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