A Simulation-based Methodology to Compare Reverse Logistics System Configuration Considering Uncertainty

With increasing environmental concerns, recovery of used products through various options has gained significant attention. In order to collect, categorize and reprocess used products in a cost and time efficient manner, a pre-evaluated network infrastructure is needed in addition to existing traditional forward logistics networks, in most cases. However, such networks, which are referred to as reverse logistics networks, impose inherent uncertainty in returned product supply and challenges additional to forward networks. Incorporating uncertainty in long term decisions with regards to network planning is significant especially in RL networks, since such decisions are difficult and costly to adjust later on. Uncertainty in product returns, dynamic and complex behavior of the system can be modeled as a queueing model, using a discrete event simulation methodology. In this work, a simulation based tool is developed which can be used as a platform for evaluating and comparing reverse logistics network configurations. In addition to defining system parameters, the tool provides experimentation with the number of collection, sorting, and processing centers, as well as the standard deviation of the return rate distribution. Various types of experiments are used in order to illustrate the use and goal of the tool, where the trade-offs within and across scenarios are addressed. Experiments are divided into three main parts; verification, pairwise detailed and a final more holistic scenario which illustrates the usage of the tool. A user interface is developed via Microsoft Excel for convenient specification of operational system parameters and scenario values. Upon running the simulation with specified experimental factors, the tool automatically computes and displays the total weighted score of each scenario, which is an indicator of the scenario quality

Methodology for evaluating LCC

Evaluating the life cycle costs (LCC) of food waste is a challenging task and few examples of previous LCC exist. This REFRESH report reviewed existing measures and methods for the evaluation of LCC of food waste. It conducted a comprehensive literature review to identify major methodological challenges related to cost modelling and externalities. The report contributes to the development of recommendations for a standardized system approach

Sustainability-Based Expert System for Additive Manufacturing and CNC Machining

The development of technologies which enable resource efficient production is of paramount importance for the continued advancement of the manufacturing industry. In order to ensure a sustainable and clean energy future, manufacturers should be able to contrast and validate existing manufacturing technologies on a sustainability basis. In the post COVID-19 era of enterprise management, the use of artificial intelligence to simulate human expert decision making abilities will open new doors to achieving heightened levels of productivity and efficiency. The introduction of innovative technologies such as CNC machining and 3D printing to production systems has redefined the manufacturing landscape in a way that has compelled users to investigate into their sustainability. For the purposes of this study, cost effectiveness, energy and auxiliary material usage efficiency have been considered to be key indicators of manufacturing process sustainability. The objective of this research study is to develop a set of expert systems which can aid metal manufacturing facilities in selecting Binder Jetting, Direct Metal Laser Sintering or CNC Machining based on viable product, process, system parameters and inherent sustainability aspects. The expert systems have been developed using the knowledge automation software, Exsys CorvidÒ. Comprehensive knowledge bases pertaining to the objectives of each expert system have been created using literature reviews and communications with manufacturing experts. An interactive environment which mimics the expertise of a human expert has been developed by the application of suitable logical rules and backward chaining. The programs have been verified by analyzing and comparing the sustainability impacts of Binder Jetting and CNC Machining during fabrication of a stainless steel 316L component. According to the results of the study, Binder Jetting is deemed to be characterized by more favorable indicators of sustainability in comparison to CNC Machining, for fabrication of components feasible for each technology

A Modeling, Optimization, and Analysis Framework for Designing Multi-Product Lignocellulosic Biorefineries

The objective of this research is to propose a methodology to develop modular decision analysis frameworks to design value chains for enterprises in the renewable fuels and chemicals sector. The decision support framework focuses on providing strategic decision support to startup and new product ventures. The tasks that are embedded in the framework include process and systems design, technology and product selection, forecasting cost and market variables, designing network capacities, and analysis of risks. The Decision support system (DSS) proposed is based on optimization modeling; systems design are carried out using integer programming with multiple sets of process and network configurations utilized as inputs. Uncertainty is incorporated using real options, which are utilized to design network processing capacity for the conversion of biomass resources. Risk analysis is carried out using Monte Carlo methods. The DSS framework is exemplified using a lignocellulosic biorefinery case study that is assumed to be located in Louisiana. The biorefinery utilizes energy crops as feedstocks and processes them into cellulosic biofuels and biobased chemicals. Optimization modeling is utilized to select an optimal network, a fractionation technology, a fermentation configuration, and optimal product recovery and purification unit operations. A decision tree is then used to design incremental capacity under uncertain market parameters. The valuation methodology proposed stresses flexibility in decision making in the face of market uncertainties as is the case with renewable fuels and chemicals. The value of flexibility, termed as “Option Value” is shown to significantly improve the net present value of the proposed biorefinery. Monte Carlo simulations are utilized to develop risk curves for alternate capacity design plans. Risk curves show a favorable risk reward ratio for the case of incremental capacity design with embedded decision options. The framework proposed here can be used by enterprises, government entities and decision makers in general to test, validate, and design technological superstructures and network processing capacities, conduct scenario analyses, and quantify the financial impacts and risks of their representative designs. We plan to further add functionality to the DSS framework and make available the tools developed to wide audience through an “open-source” software distribution model

Techno-economic evaluation of integrated process flowsheets for vinasse management with value addition for decision making

Bioethanol production through fermentation of sugarcane juice and its derivatives such as molasses is gaining popularity worldwide as focus shifts towards renewable energy production. However, ethanol fermentation results in the production of large volumes of a dark brown and low pH liquid waste termed vinasse. At a vinasse production rate of 12-15 liters per liter of ethanol, sustainability of this bioprocess is impacted as effluent handling costs are high. If disposed onto the land, breakdown of the organic matter within may lead to the release of greenhouse gases into the atmosphere. Additionally, disposal into water bodies results in eutrophication due to the overload of plant nutrients (N, P and K). Further, owing to the high potassium content, the use of dewatered vinasse as animal feed supplements has been shown to cause digestive tract problems in ruminants depending on the supplementation rates (>10%). To increase sustainability of bioethanol fermentation processes through combined treatment and resource recovery from vinasse, biological and physico-chemical processes have been developed and implemented in industry. Conventionally, raw vinasse is dewatered through evaporation processes (MEE) as a means of volume reduction. Membrane processes such as reverse osmosis (RO) have in the recent past become popularized as water recovery options from vinasse due to process simplicity and lower costs of equipment. Resulting concentrates from RO and MEE can be used as fertilizer. Due to the high organic content, vinasse is a suitable candidate for anaerobic digestion (AD) where the organic matter is broken down to biogas and an effluent that can be safely used as fertilizer. Additionally, the biogas from AD may be harnessed for electricity generation through combined heat and power processes or upgraded to biomethane to be used as a substitute for natural gas. For high moisture content substrates such as vinasse, up flow anaerobic sludge blanket reactors are best suited as sludge residence time is prolonged thereby increasing contact time with substrate which leading to higher methane yields. AD is often sensitive to changes in temperature, substrate composition, loading rate and pH. The presence of inhibitory components such as potassium salt ions (>11.6 g/L) in the vinasse feed result in a reduction of methanogenic activity manifested through reduced biogas and methane yields. Salt recovery processes including electrodialysis and ion-exchange have been investigated in literature on a pilot scale for the removal of K+ ions from raw vinasse. To improve resource productivity, integration of vinasse treatment processes has been implemented in industry. Integration combines biological and physico-chemical processes which results in performance optimization and energy efficiency thereby improving economic feasibility of the projects. During the project conceptualization phase, process modelling is a vital tool that can be used to predict outcomes such as substrate utilization rates, product yields and optimal operating conditions of integrated processes in a timely and cost effective manner. In addition, techno-economic analyses can be used to determine cost sensitive areas and overall feasibility of the integrated processes. Having reviewed the current industrial practices, this project sought to develop integrated flowsheets consisting of biological and physical processes for the combined vinasse treatment and value creation. Value creation was demonstrated through the recovery of valuable products including energy, salts and water from the raw vinasse. Due to its simplicity and cost effectiveness, AD was selected as the primary technology for vinasse treatment and biogas production. This was coupled with a combined heat and power system for electricity generation to form the base case flowsheet. It was hypothesized that incorporation of pre- and post-treatment as well as alternative biogas utilization processes to the base case flowsheet for recovery of salts and water would generate additional revenue and cost savings. Profitability of the base case process was expected to increase with the additional pre- and post-treatments. To fulfil the objective set out and prove the hypothesis, a three step research approach was taken. The first step involved simulation and benchmarking of the base case flowsheet (AD and CHP). Using techno-economic analyses, the effect of individual addition of pre- and post-treatment options to the base case flowsheet on profitability was investigated. A framework was then developed to investigate the incorporation of combined pre- and posttreatment options to the base case flowsheet. Thereafter, a decision support tool that in comparing various combinations of vinasse treatment routes in terms of process performance and profitability was developed to aid in the synthesis of vinasse treatment processes in industry. As bioprocess modelling is complex, it was important to select an appropriate simulation platform. Given the availability of a dedicated bioprocess compound database, sensitivity and optimization features and flexible customization options within Aspen Plus, it was preferred as the primary simulation platform over SuperPro Designer and high performance programming languages (C++, Java). In developing the base case AD flowsheet, several frameworks in the literature were considered. These included ADM1 (Batstone et al., 2002), ADM-3P (Ikumi et al., 2011) and a comprehensive model by Angelidaki et al. (1993). The presence of a well defined stoichiometric framework motivated the decision to adopt the comprehensive model by Angelidaki et al. (1993). Using a combination of in-built unit operations as well as customized user models (calculator blocks), the AD model by Angelidaki et al. (1993) was implemented on Aspen Plus. As ADM1 was considered an extension of the comprehensive model (Angelidaki et al., 1993) with several similarities, kinetic constants describing substrate uptake and microbial growth were adapted from ADM1. To ascertain the predictive quality of the built AD model, four case studies in the literature concerning the AD of manure (cow and swine) and municipal solid waste were simulated and the predicted simulation results compared to the experimental results. The developed AD model accurately predicted the methane yields of the four case studies as evidenced by the average difference of 10% between simulation and experimental results. A regression analysis between experimental and predicted data yielded a value of 0.74. Given the assumptions made in simplifying the developed model, the R2 value was deemed acceptable and further affirmed the agreement between the model and experimental results. To investigate the robustness of the developed AD model, sensitivity analyses on the feed composition as well as organic loading were conducted. Increasing inhibitory compound concentrations above certain thresholds was shown to negatively impact methanogenic activity as evidenced by the decreasing methane yields. Although ammonia is inhibitory at concentrations above 0.22 g/L, it is an important nitrogen source for biomass growth. Similarly, while acetic acid is inhibitory to acetogenic microbes, it is a crucial substrate for the growth of methanogenic archaea and methane production. Inorganic salt inhibition on the other hand may be reduced through extraction of K2SO4 through pre-treatment processes. The compositional sensitivity analyses as well as the benchmarking study showed that the built AD model had a solid core framework which accurately predicted experimental data for a range of substrates. Combined with a simplified CHP model of a Jenbacher spark ignition engine (General Electric, 2008) to form the base case flowsheet, the built AD model was used for all further simulations in this work. To determine the financial standing of the base case, simulation and subsequent techno-economic analyses were conducted. At an industrial reactor capacity of 2000 m3 and a loading rate of 25 kgCOD/m3 .day, simulation of the base case process resulted in a methane yield of 45 L-CH4/kgVSadded and an electrical production capacity of 410 kW. Discounted cash flow analyses (USD, 2016) showed that the base case was not profitable within a 20-year project lifetime as evidenced by the low return on investment and internal rate of return. However, a further sensitivity on profitability of the base case showed that decreasing potassium ion concentrations in the feed would result in higher profitability higher methane yields because of decreased K+ inhibition. Despite the positive effect of on AD performance, further analyses were required to validate feasibility of K2SO4 recovery processes as well as water recovery processes aimed at further value creation from vinasse. To investigate the effect of pre-treatment on base case flowsheet economics, an ion exchange process adapted from Zhang et al. (2012) was incorporated based on the comparatively higher degree of selectivity to K+ ions exhibited by the ion exchange process than ozonation and electrodialysis. As expected, improved CH4 yields (14%), electrical production and consequently, increases (>100%) in profitability indicators were observed. However, the pretreated base case (IEX-AD-CHP) remained unprofitable which was an indication that the marginal revenue from increased electrical production and K2SO4 sales did not match the additional capital costs. To increase profitability of the base case, biogas upgrading using a HPWS system was used in place of the CHP. Due to the comparatively low cost of HPWS equipment coupled with the increased revenue from biomethane sales, the AD-HPWS process exhibited higher profitability (ROI: 19.6%) than the base case (ROI: 0%). As evidenced by the IRR (16.3%) that was greater than the cost of capital (15%), the AD-HPWS option was profitable over a 20 year lifetime. Resource recovery from the AD effluent was sought through incorporation of RO and MEE to form the AD-CHP-RO and AD-CHP-MEE routes. Most notably, there was a significant (170%) increase in cost savings with the use of RO and MEE concentrates as fertilizer compared to the raw AD effluent from the base case. Additional cost savings of up to $27 700 were achieved with upstream reintegration of RO permeate or MEE condensate water. This savings was based on the municipal water tariff of R5/kL. The combined cost savings led to increased profitability of the base case as evidenced by the increase in ROI from 0$250 000/yr) and upstream reintegration of water. This led to the conclusion that the recovery of concentrates from vinasse is an important decision criterion when looking to increase profitability and process sustainability. Overall, based on the techno-economic analyses, the most profitable vinasse treatment process included an anaerobic digester coupled with a high-pressure water scrubbing system for biomethane production and reverse osmosis process for water recovery (ROI: 22.9%, NPV: $540 000). This facilitated both increased energy output from biomethane and cost savings from water reuse. Further research is recommended around the AD modelling aspect to extend functionality to ionic speciation and pH prediction. it is recommended that equipment quotes from suppliers within South Africa be sourced as opposed to costing heuristics in the literature to increase the accuracy of capital and operating expenditure

Implementation of design for environment principles in product development using a case study on the design of a passenger car door

Product design is a complex process that requires design engineers taking into consideration а number of factors simultaneously. Though the primary aim is to fulfil a given function in a cost effective manner, in recent years considerable emphasis has been placed on designing products that result in minimal negative environmental impact. In the past, research has focussed on developing tools that assist designers in selecting suitable materials and manufacturing processes in the early stages of product design itself. A correct choice of materials can have a significant impact on promoting Design for Environment (DfE) and determining suitable End of Life (EoL) strategies such as recycling, reuse and remanufacture. This dissertation highlights the importance of implementing design aspects such as Design for Assembly (DfA) and Design for Disassembly (DfD). Included is a case study which illustrates the benefits of implementing DfD in the design of a passenger car door. Through a prudent selection of suitable materials, manufacturing processes and also joining and dismantling techniques, the overall sustainability of the product can been increased. It is seen that in order to incorporate DfE principles in product design, the designers must deal with vast amounts of data simultaneously. Dealing with such large quantities of data can be tricky. This dissertation proposes arranging materials, manufacturing processes and assembly and disassembly techniques in the form of an ontology so that designers can have access to design information in a systematic and precise format. The principles to construct a DfE tool that assists design engineers not only select suitable materials, manufacturing processes and assembly/disassembly methods, but also helps analyse every stage of the product’s life and measure its impact on the environment during the initial stages of design itself have been provided in this dissertation

Environmentally conscious design : an economic life cycle approach

Companies are under increasing pressure to deal with environmental concerns during product design, for it is the design process which primarily decides the environmental impact of a manufactured product over its life. Tools which assist in taking a life cycle view of the product are a necessary support to designers. Prime amongst these tools is Life Cycle Assessment (LCA). However, a major criticism of LCA methodologies is that while they provide advice on environmentally superior product designs, they do not provide guidance on the economic impact. With product take back increasingly likely to become the responsibility of producer companies attention is now being paid to the later phases of a products life, such as maintenance and disposal costs. A new methodology is shown to be required to complement LCA, one which considers the economic implications of environmentally superior designs over the whole product life. It is argued that a major challenge of such a methodology will be how it deals with the uncertainty associated with the future. The research provides a review of product life cycle design methodologies and a critique of existing approaches to uncertainty. A design teams requirements for decision support that deals with product economic life cycle uncertainty is presented and a decision support methodology which meets these requirements is described. The methodology builds upon the theory of life cycle costing. In practice, the methodology integrates a computer based life cycle model with statistical techniques to quantify the contribution of life cycle variables. In bringing these proven but previously separate tools together the method resolves the issue of uncertainty in a novel and acceptable way. Through the use of an in-depth industrial case study, it is shown that the methodology provides practical support to the design team to produce economically superior product life cycle designs

EPA Guidelines for Regulatory Impact Analysis

On February 17, 1981, the President issued Executive Order 12291 mandating that regulatory agencies must prepare regulatory impact analyses (RIAs) on all major regulations. Before taking action, the agencies must send all RIAs and proposed regulations to the Office of Management and Budget (OMB) for review. These guidelines discuss the analytical techniques that may be used and the information to be developed by the U.S. Environmental Protection Agency when (l) stating the need for the proposed regulatory action; (2) examining alternative approaches to the problem; (3) quantifying benefits and costs and valuing them in dollar terms (where feasible); and (4) evaluating the findings on benefits, costs, and distributional effects. This document provides guidance for preparing Regulatory Impact Analyses. It includes four appendices and one supplement in addition to the main document.

Multicriteria analysis for retrofitting of natural gas melting and heating furnaces for sustainable manufacturing and industry 4.0

Different retrofitting measures can be implemented at different levels of the industrial furnace, such as refractory layers, energy recovery solutions, new burners and fuel types, and monitoring and control systems. However, there is a high level of uncertainty about the possible implications of integrating new technologies, not only in the furnace but also on the upstream and downstream processes. In this regard, there is a lack of holistic approaches to design the optimal system configurations under a multicriteria perspective, especially when innovative technologies and multi-sectorial processes are involved. The present work proposes a holistic approach to natural gas melting and heating furnaces in energy-intensive industries. A multicriteria analysis, based on criteria and subcriteria, is applied to select the most profitable retrofitting solution using the analytic hierarchy process and stakeholder expertise. The methodology is based on technical indicators, i.e., life cycle assessment, life cycle cost, and thermoeconomic analysis, for evaluating the current state of existing natural gas furnaces. Once the current state is characterized, the methodology determines the potential of efficiency improvement, environmental impact reduction, and cost-savings caused mainly by the implementation of new retrofitting solutions including new refractories, new burner concepts (co-firing), and innovative energy recovery solutions based on phase change materials. Therefore, this methodology can be considered as the first stage that guarantees technical, environmental, and economic feasibility in evaluating the effects of new technologies on the overall system performance