Closed-loop Production Systems Research Articles

Internet-of-Things framework for scalable end-of-life condition monitoring in remanufacturing

The worldwide generation of waste electrical and electronic equipment is continuously growing, with electric vehicle batteries reaching their end-of-life having become a key concern for both the environment and human health in recent years. In this context, the proliferation of Internet of Things standards and data ecosystems is advancing the feasibility of data-driven condition monitoring and remanufacturing. This is particularly desirable for the end-of-life recovery of high-value equipment towards sustainable closed-loop production systems. Low-Power Wide-Area Networks, despite being relatively recent, are starting to be conceived as key-enabling technologies built upon the principles of long-range communication and negligible energy consumption. While LoRaWAN is considered the open standard with the highest level of acceptance from both industry and academia, it is its random access protocol (Aloha) that limits its capacity in large-scale deployments to some extent. Although time-slotted scheduling has proved to alleviate certain scalability limitations, the constrained nature of end nodes and their application-oriented requirements significantly increase the complexity of time-slotted network management tasks. To shed light on this matter, a multi-agent network management system for the on-demand allocation of resources in end-of-life monitoring applications for remanufacturing is introduced in this work. It leverages LoRa’s spreading factor orthogonality and network-wide knowledge to increase the number of nodes served in time-slotted monitoring setups. The proposed system is validated and evaluated for end-of-life monitoring where two representative end-node distributions were emulated, with the achieved network capacity improvements ranging from 75.27% to 249.46% with respect to LoRaWAN’s legacy operation. As a result, the suitability of different agent-based strategies has been evaluated and a number of lessons have been drawnaccording to different application and hardware constraints. While the presented findings can be used to further improve the explainability of the proposed models (in line with the concept of eXplainable AI), the overall framework represents a step forward in lightweight end-of-life condition monitoring for remanufacturing.

Life Cycle Assessment of Tomato Cultivated in an Innovative Soilless System

The main goal of this study is to present the life cycle assessment results of an innovative closed-loop production system, called an agriponic system, used for producing tomatoes. In the study, this new system is presented, as well as its related environmental impacts generated for the production of the tomatoes. A life cycle assessment (according to ISO 14040) was applied to it, from seedling purchase and planting to harvest, using a functional unit of 1 ton of cherry tomatoes produced. SimaPro 9.3.0.3 software and the Ecoinvent database were used to analyze five impact categories. Plant growth emerged as the process unit with the highest impact, particularly for the ozone depletion potential (ODP), with a value of 0.00056 kgCFC-11eq, and for photochemical oxidation (POCP), with a value of 0.0784 kgC2H4eq impact categories. Greenhouse climate management presented a significant impact to the acidification potential (AP), with a value of 1.021 kgSO2eq. Conversely, the phases of plant transplanting, harvesting, and crop disposal had positive impacts for all impact categories considered in the study, because they were very low. In conclusion, agriponic greenhouse tomato production is a sustainable process. This is due to fewer pesticides that are used, and to nutrient solution reuse.

Conceptualizing data-driven closed loop production systems for lean manufacturing of complex biomedical devices—a cyber-physical system approach

A model is presented for shifting the manual intensive manufacturing process of complex biomedical devices towards more lean and efficient production process via application of concepts of cyber physical systems in combination with big data and analytics in a closed loop manner. The concept model is capable of handling high product volumes and variety, has ability for self-adaptation and correction in various operating conditions, and offers real-time quality control. The approach acknowledges the challenge of these industries operating in a strict regulated environment and the higher standards of built-in quality required by developing a closed loop process, proposed to be built in accordance to the requirements of regulatory bodies and current Industry 4.0 practices. The proposed model illustrates that modern manufacturing methodologies and concepts can be integrated and adopted in such highly regulated manufacturing environments and that the model can be deployed to different production scenarios.

Sustainable citric acid production from CO2 in an engineered cyanobacterium.

Citric acid is one of the most widely used organic acids in the world, with applications ranging from acidity regulation in food and beverages to metal chelation in hydrometallurgical processes. Most of its production is currently derived from fermentative processes, using plant-derived carbon feedstocks. While these are currently dominant, there is an increasing need to develop closed-loop production systems that reduce process carbon footprint. In this work, we demonstrate for the first time that an engineered marine cyanobacterium Synechococcus sp. PCC 7002 can be used as a sustainable chassis for the photosynthetic conversion of CO2 to citric acid. Decreased citric acid cycle flux, through the use of a theophylline-responsive riboswitch, was combined with improved flux through citrate synthase and enhanced citric acid excretion, resulting in a significant improvement to citric acid production. While allowing citrate production, this strategy induces a growth defect which can be overcome by glutamate supplementation or by fine-tuning aconitase levels, resulting in an increase in production relative to WT of over 100-fold. This work represents a first step toward sustainable production of a commodity organic acid from CO2.

Gaussian Process Surrogate Modeling Under Control Uncertainties for Yield Prediction of Carbon Nanotube Production Processes

Abstract A large-scale production of carbon nanotubes has been of great interest due to their practical needs, which is limited by the difficulty of producing them with controlled structures and properties. We seek for a surrogate modeling to predict the process yield for a given process configuration under control uncertainties. The predictive power can be used to optimize the process configuration in a closed-loop production system. A challenge in the surrogate modeling is that some process conditions are controlled by other manipulating factors, and the control precision is not high. Therefore, the process conditions vary significantly even under the same setting of the manipulating factors. Due to this variation, the surrogate modeling that directly relates the manipulating factors to the process outcome does not provide a great predictive power on the outcome. At the same time, the model relating the process conditions to the outcome is not appropriate for the prediction purpose because the process conditions cannot be accurately set as planned due to the control uncertainties for a future process run. Motivated by the example, we propose a two-tiered Gaussian process (GP) model, where the bottom tier relates the manipulating factors to the process conditions with control variation, and the top tier relates the process conditions to the outcome. It explicitly models the propagation of the control uncertainty to the outcome through the two modeling tiers. The benefits of the approach over the standard GP approach are illustrated with multiple simulated scenarios and carbon nanotube production processes.

The bio-based economy, 2030 Agenda, and strong sustainability – A regional-scale assessment of sustainability goal interactions

Policy-makers face the challenge of assessing and implementing sustainability measures, while also dealing with parallel and sometimes conflicting policy agendas, long-term policy impacts, and contested interpretations of sustainability. To support evidence-based decision-making in this context, this paper presents the results from an integrated assessment of sustainability goal interactions. Links between the bio-based economy, the 2030 Agenda, and the so-called strong sustainability paradigm were explored in a regional-scale case. The analysis focused primarily on developments in the forestry and energy sectors. Direct trade-offs and synergies as well as broader systemic impacts were identified. The results show how goals from the bio-based economy, 2030 Agenda and strong sustainability paradigm are mutually interacting. Positive interactions were found within two clusters of goals, offering coherent and synergetic transition pathways within these. The first cluster encompasses developments toward intensified forestry, renewable energy, and closed-loop production systems. The second pathway supports diversified forestry and protection of critical natural capital. However, while internally coherent, trade-offs were identified between these goal clusters, demonstrating the difficulty in simultaneously making progress on goals belonging to different sustainability agendas. The results also stress the need for disaggregation and long-term assessments to identify trade-offs and synergies. Finally, the analysis highlights the theoretical potential but practical challenges of implementing the bio-based economy and 2030 Agenda in a way that adheres to strong sustainability. The analytical framework used in the present study may be adapted and applied to other decision-making contexts. It is particularly useful in settings characterized by uncertainty and unstructured problem spaces.

Recirculating water and nutrients in urban agriculture: An opportunity towards environmental sustainability and water use efficiency?

Urban agriculture systems, such as rooftop greenhouses, are attractive alternatives for mitigating the impacts of the extensive food supply chains that currently feed cities. In this study, we study the opportunity that nutrient recirculation offers to improve the environmental performance of agricultural systems. In particular, we analyze the environmental burdens of a hydroponic closed-loop production system that recovers nutrients and reduces water demand by recirculating the irrigation water leaching from the substrate bags along with nutrients that have not been assimilated by the plant. The closed-loop system is compared to a linear system in which there is no nutrient or water recovery. Based on two green bean crop cycles in a Mediterranean rooftop greenhouse, we analyze the yield, climatic variables and water and nutrient balances, and apply life cycle assessment (LCA) to study the environmental impacts.The results of this study indicate that closed-loop systems save daily 40% of irrigation water and between 35 and 54% of nutrients. Moreover, leachate reuse leads to reduced eutrophication impacts, but it can entail nutrient deficiencies. However, implementing a closed-loop system requires additional infrastructure causing larger impacts than linear systems in terms of global warming and fossil resource scarcity. The results of the LCA were highly sensitive to the yield, the crop production period and the meteorological conditions. Based on these results, we design improved scenarios, providing recommendations for reducing the impacts of closed-loop systems for more sustainable cities.

Sustainable Management of Remanufacturing in Dynamic Supply Chains

Closed-loop production systems encompass all processes for returning, remanufacturing, recycling, discarding, and repackaging products. These elements form the core of sustainable manufacturing by managing what otherwise would be waste to enable reuse and by controlling its associated pollution. This paper presents the general management model of sustainable remanufacturing within a dynamic closed-loop supply chain. Our specification encompasses agents positioned at key stages in the supply chain, e.g., manufacturers, retailers, and customers, and considers both profitability and environmental performance of their decentralized decisions. We cast the problem to allow for interdependence of agents through a Nash game. These salient features simultaneously render the mathematical model more realistic and computationally challenging. To proceed, our model is formalized by using variational inequalities, which in turn are converted to a fixed point problem that we solve using a computationally tractable algorithm. Decision rules for strategic remanufacturing and recycling are provided to complement the numerical solution in an illustrative example.

Developing a Closed-Loop Water Conservation System at Micro Level Through Circular Economy Approach

A closed loop system for micro-level conservation of fresh water at household user point has been developed in this work in a comprehensive circular economy (CE) framework encompassing technical, environmental and economic aspects in a concurrent manner. The system has been developed through field survey of households in an urban setting in Indian context and experimental investigation on membrane filtration and recirculation of grey water generated from domestic use like cooking, bathing, washing etc. Pollution load of the grey water utilized in the sample involved high alkalinity (pH = 9.00), total suspended solid (TSS = 536 mg/L), odour (TON 2). Membrane based filtration process has been developed to ensure that the reclaimed water is of acceptable quality as alkalinity decreases to 7.2, TSS reduces to 95 mg per litre and odour in terms of TON reduces to one. Economic feasibility of implementing such a system is assessed by cost benefit analysis. Estimated annualized total cost (capital and operating) for treating and reusing a cubic meter of waste water in this CE framework amounts to US $1.5 only. Preference score derived from utility estimates of conjoint analysis (CA) reveal that consumers have positive attitude to accept water conservation strategy in circular economy framework. The ideal composition of reclaimed grey water to be preferred is odourless (TON value near 1), low TSS (less than 102 mg/L) and neutral pH (nearly7.00) The study reveals that about half of fresh water demand per day per capita can be saved by developing a closed-loop production system at micro level, where grey water generated as waste from domestic use is not discharged as followed in traditional open-ended economic model. Instead of take-make-use-discharge, waste water is added in the production system as a resource. After applying an advanced cost-effective clean technology, grey water is kept in a material loop and usage creating further value for a longer period. Sustainable water system development by this holistic circular water conservation approach is no longer an option but a necessity to protect the life-sustaining valuable freshwater resource. Developing water conservation system in closed-loop model provides a novel solution as it will yield positive and significant utility and economic value in a very cost effective green design.

Analysis of Closed Loop Production System Using Orthogonal Array and Integer Programming Optimization

Sustainable production systems require optimal utilization of resources. Raw material acquisition is one of the costly processes in a production system. EOL (End-of-Life) products re-manufacturing through reverse logistics can help in decreasing excessive raw material cost. In this study, we consider production system of closed loop supply chain in which both forward and reverse production systems are active. DOE (Design of Experiments) methodology is incorporated which is a statistical approach adopted in dealing with complex workplace problems. We employ L9 orthogonal array using Taguchi experiment in Minitab 17 and DOE for plotting the results. Dependent variables used in this study are productivity, P (number of forward and reverse products produced per period) and quality accuracy of product (measured in percent deviation from reference standards). A trade-off analysis between the control variables is presented on the basis of SNR (Signal to Noise Ratio). Control variables used in the analysis are tools employed in production system (tu), number of machines being used (m) and dedicated manufacturing cells (dc). We use three levels of analysis for each control factor. Optimum result conditions are calculated using signal to noise ratio with larger-the-better-criteria as well as smaller-the-better criteria and study is concluded with main effects of the mean plots. DOE optimization analysis for productivity suggests combination set of 32, 8, and 6 for tools, machines in use and manufacturing cells, respectively. Similarly, for optimal dimensional accuracy, tools used are 24; number of machines in use is 14 with 3 manufacturing cells. All result indices are accomplished within a confidence interval of 95% with p-values less than 0.05. MILP (Mixed Integer Linear Programming) analysis considers cost function of production and transportation between tools, machines and levels and Taguchi based experimental findings are validated by mathematical optimization findings.

A Joint Production and Maintenance Optimization of Closed-Loop Production System under Carbon Emission with a Switching Subcontractor Consideration

This study outlines a new forecasting problem of closed-loop production system under environmental aspect by proposing a new solution based on subcontracting. By studying the impact of the carbon tax on decision-making of production optimization, we propose an original economic production and maintenance strategies to minimize the total cost. Additionally, to reduce the total quantity of carbon and its tax, the subcontractor has a role to help either manufacturing or remanufacturing unit during the process of production. Indeed, the principle objectives are to determine the economic production plans for manufacturing, remanufacturing and subcontracting units as well as the optimal maintenance planning characterized by the optimal number of preventive maintenance actions for manufacturing unit, minimizing the total cost of production, inventory, carbon penalty and maintenance.

Optimization of a closed‐loop HHO production system for vehicles and houses

This study focused on determining the optimal conditions for producing by electrolysis HHO that is suitable for use in motor vehicles and in households. The experiments used electrolyte concentrations of 0.50%, 0.75%, 1.00%, 1.25%, and 1.50% w/w KOH (aq.), and 316 L stainless steel 20 × 30 mm electrode plates. The gap between the plates was adjusted to 1, 3, 5, 7, and 9 mm, and experiments were conducted at the steady state temperatures of 40°C, 45°C, 50°C, 55°C, 60°C, 65°C, 70°C, 75°C, 80°C, 85°C, 90°C, and 95°C, for 10 min. It was found that the optimized production conditions for houses or motor vehicles, according to this study, were 7 mm cell gap and 1.50% w/w KOH at 90.0°C ± 1.0°C operating temperature, or 5 mm cell gap and 1.25% w/w KOH at 85.0°C ± 1.0°C operating temperature, respectively. To apply this research to real operation, the methods of real application with vehicles and household appliances were discussed. © 2018 American Institute of Chemical Engineers Environ Prog, 38: 268–277, 2019

Adaptation of the Product Structure-based Integrated Life cycle Analysis (PSILA) technique for carbon footprint modelling and analysis of closed-loop production systems

In a previous work, the Product Structure-based Integrated Life cycle Analysis (PSILA) technique was developed to conduct cost modelling and analysis of closed-loop production systems. In this paper, we expand the utility of this technique into carbon footprint (CFP) modelling and analysis of closed-loop production systems – enabling companies to make informed decisions on whether to adopt closed-loop production based not only on economic but also environmental performance. A description of the PSILA technique applied for carbon footprint modelling and analysis is explained, followed by a case study of closed-loop production of a flat-panel display (FPD) monitor to validate the technique. We verified the CFP result simulated by the model built through the PSILA technique, or PSILA-CFP model in short, against the result generated by a model built through the conventional Life Cycle Assessment (LCA) method. A benchmarking analysis was then conducted to compare the closed-loop production system against the linear production system. Through this analysis, we demonstrated how the CFP result can be broken down based on the product structure, thus enabling us to granularise the result and trace the impact of implementing a closed-loop production system to the individual modules, components and materials that are recovered, reutilised or treated in the system. The results were able to show that the implementation of the closed-loop production system for the FPD monitor can potentially result in an overall CFP reduction of 39.91 million kg CO2e, of which 90.03% is contributed by the closed-loop recycling of ABS. The other significant contributors of CFP reduction are from the closed-loop material recycling of the aluminium, which accounts for 8.13 million kg CO2e or 20.37% of the total CFP reduction. A sensitivity analysis was also carried out to investigate the effects of data uncertainties, which may invalidate assumptions made in the case study. In summary, we have successfully adapted the PSILA technique so as to provide decision support in the form of analytical insights on how a closed-loop production system will perform in terms of carbon footprint, why it performs this way and what to look out for if the decision is made to implement such a system.

Improvement of the evaluation of closed-loop production systems with unreliable machines and finite buffers

A closed-loop production system, or loop, is a system in which a constant amount of material flows through a single fixed cycle of workstations and storage buffers. Manufacturing processes that utilize pallets or fixtures can be viewed as loops. Control policies such as CONWIP and Kanban create conceptual loops. Gershwin and Werner (2007) developed a decomposition algorithm that accurately evaluates Buzacott type closed-loop systems of any size. However there are cases where the evaluated production rate, as a function of some system parameter, is discontinuous. Such a discontinuity may give misleading results for loop system design and optimization method. We present two modifications that improve the algorithm of Gershwin and Werner (2007). Two new special types of two-machine one-buffer building blocks are developed for the decomposition, and analytical solutions for them are found. Numerical experiments are provided to show the improvement of the evaluation accuracy as compared with the existing algorithm. The discontinuity in production rate is greatly diminished with these modifications.

Product Structure-Based Integrated Life Cycle Analysis (PSILA): a technique for cost modelling and analysis of closed-loop production systems

Abstract As closed-loop production becomes an increasingly viable strategy for product life cycle management, cost modelling and analytical tools for closed-loop production systems will become increasingly important. Existing tools based on life cycle costing (LCC) methods are lacking an integrated life cycle perspective in their approach – a perspective that cannot be overlooked when modelling closed-loop production systems. In this paper, we aim to solve this lack of integrated life cycle approach by proposing the product structure-based integrated life cycle analysis (PSILA) technique. It allows us to streamline the process of modelling a closed-loop production system for a complex product based on its product structure. Through this technique, we developed a cost model of a closed-loop production system for a flat-panel (FPD) monitor case study. In this case study, the results simulated by the cost model show an increase in the economic performance when closed-loop production is adopted for the FPD monitor. Deeper analysis of the results in the case study indicate that in order to improve the economic performance of the closed-loop production system for the FPD monitor, the best strategy is not to merely focus on the reutilisation of materials. Instead, the option to remanufacture the FPD monitor for the secondary market should be explored to maximise the value reclaimed from the monitors in the EoL phase. The case study demonstrates that the cost model developed through the PSILA technique has the ability to function as a tool for analysing the economic performance of closed-loop production systems. More importantly, it has the ability to provide us with strategic insights on the cost feasibility of adopting closed-loop production strategies.

Modelling and Design of Closed-Loop Manufacturing Systems

This paper introduces an analytical method for evaluating the performance of closed loop manufacturing systems with unreliable machines and finite buffers. The method involves transforming an arbitrary loop into one without thresholds and then evaluating the transformed loop using a new set of decomposition equations. It is more accurate than existing methods and is effective for a wider range of cases. The convergence reliability, and speed of the method are also discussed. In addition, observations are made on the behavior of closed loop production systems under various conditions. Finally, the method is used in a case study to design a flexible manufacturing system for production of aerospace parts.

Robust optimal dynamic production/pricing policies in a closed-loop system

Hybrid manufacturing/remanufacturing systems play a key role in implementing closed-loop production systems which have been considered due to increasingly environmental concerns and latent profit of used products. Manufacturing and remanufacturing rates, selling price of new products, and acquisition price of used products are the most critical variables to optimize in such hybrid systems. In this paper, we develop a dynamic production/pricing problem, in which decisions should be made in each period confronting with uncertain demand and return. The manufacturer is able to control the demand and return by adjusting selling price and acquisition price respectively, also she can stock inventories of used and new products to deal with uncertainties. Modeling a nominal profit maximization problem, we go through robust optimization approach to reformulate it for the uncertain case. Final robust optimization model is obtained as a quadratic programming model over discrete periods which can be solved by optimization packages of QP. A numerical example is defined and sensitivity analysis is performed on both basic parameters and parameters associated with uncertainty to create managerial views.

Closed-loop production systems—A sustainable supply chain approach

Closed-loop production systems strive for sustainability by improving economic and environmental goals simultaneously. We note that many negative environmental impacts, such as waste, energy consumption, transport processes and packaging, can be avoided if companies establish closed-loop production systems. In this contribution we outline the concept of sustainable supply chain networks (SSCN) as a suitable means of designing closed-loop production systems. The implementation of SSCN allows the process links between the companies in a supply chain to close, which facilitates the transformation from a flow economy into a circular economy. A circular economy improves sustainability and ultimately leads to improvements in economic and environmental performance.

A decomposition approximation for three-machine closed-loop production systems with unreliable machines, finite buffers and a fixed population

This paper describes an approximate analytical method for evaluating the average values of throughput and buffer levels of closed three-machine production systems with finite buffers. The method includes a new set of decomposition equations and a new building block model. The machines have deterministic processing times and geometrically distributed probabilities of failure and repair. The numerical results of the method are close to those from simulation. The method performs well because it takes into account the correlation among the numbers of parts in the buffers. Extensions to larger systems are discussed. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Appendix of additional numerical results]

Performance analysis for closed-loop production systems with unreliable machines and random processing times

In this study, we propose some simple but effective throughput-approximation methods for finite-buffered closed-loop production systems with unreliable machines and exponentially distributed processing times. The proposed approximation methods are based on decomposition and aggregation principles. According to the method representing the decomposed systems, three different approximation methods are developed, along with a simple upper bounding method for throughputs. Extensive computational experiments are performed to show the effectiveness of the approximation and upper bounding methods.