Maintenance-based strategies for environmental risk minimization in the process industries

Industry, environmental agencies and the scientific community have all emphasized the need to include environmental impact considerations next to profitability objectives in the design phase of modern chemical processes, responding to the increasing social concern over environmental degradation in the past years. Most environmental impact assessment and minimization approaches, however, are rather qualitative, providing general guidelines. In this work, to overcome their limitations and rigorously represent the defining elements of environmental risk, i.e. the mechanism of occurrence of unexpected events usually related to equipment failure and the severity of their consequences, detailed process, reliability and maintenance characteristics are incorporated within a process optimization framework. The objective concerns the optimization of overall process performance defined as a system effectiveness vector characterized by both the environmental and the profitability functions of the system. Implementation of the framework on a process example identifies the optimal combination of process design and operation as well as preventive maintenance strategies that accomplish the conflicting environmental and profitability targets and quantifies the existing trade-offs between them.     

Process design for the environment: A multi-objective framework under uncertainty

 Designing chemical processes for the environment requires consideration of several indexes of environmental impact including ozone depletion, global warming potentials, human and aquatic toxicity, photochemical oxidation, and acid rain potentials. Current methodologies, such as the generalized waste reduction algorithm (WAR), provide a first step towards evaluating these impacts. However, to address the issues of accuracy and the relative weights of these impact indexes, one must consider the problem of uncertainties. Environmental impacts must also be weighted and balanced against other concerns, such as their cost and long-term sustainability. These multiple, often conflicting, goals pose a challenging and complex optimization problem, requiring multi-objective optimization under uncertainty. This paper will address the problem of quantifying and analyzing the various objectives involved in process design for the environment. Towards this goal, we proposed a novel multi-objective optimization framework under uncertainty. This framework is based on new and efficient algorithms for multi-objective optimization and for uncertainty analysis. This approach finds a set of potentially optimal designs where trade-offs can be explicitly identified, unlike cost-benefit analysis, which deals with multiple objectives by identifying a single fundamental objective and then converting all the other objectives into this single currency. A benchmark process for hydrodealkylation (HDA) of toluene to produce benzene modeled in the ASPEN simulator is used to illustrate the usefulness of the approach in finding environmentally friendly and cost-effective designs under uncertainty. Received: 8 February 2000 / Accepted: 10 March 2000     

Pollution prevention through process integration

 Process integration is a holistic approach to process design and operation. It emphasizes the unity of the process units and objectives. Therefore, it provides a unique framework for integrating environmental issues with other process objectives such as profitability, yield enhancement, debottlenecking and energy reduction. This paper presents a review of recent advances in the area of pollution prevention through process integration. First, the alternative methods for industrial waste reduction are discussed. Then, process integration is defined and categorized into three main components: synthesis, analysis and optimization. Next, mass integration science and methods are reviewed with special emphasis on their critical role in pollution prevention. Throughout the paper, various tools and techniques are described and illustrated. Received: 7 July 1998 / Accepted: 8 September 1998     

A multi-objective fuzzy graph approach for modular formulation considering end-of-life issues

Increased awareness of the negative environmental impact caused by electronic waste has driven electronics manufacturers to re-engineer their product design process and include product end-of-life considerations into their design criteria. Design for the Environment (DfE), as a possible solution, lacks an implementation framework. To address this problem, a fuzzy graph based modular product design methodology is developed to implement DfE strategies in product modular formulation considering multiple product life cycle objectives guided by DfE. A fuzzy connected graph approach is used to present the product structure, whereby fuzzy relationship values are determined by applying Analytic Hierarchy Process (AHP) to life cycle environmental objectives along with other functional and production concerns. Based on the fuzzy connected graph, an optimal modular formulation is searched using the graph-based clustering algorithm to identify the best module configuration. An example is provided to illustrate the methodology and the algorithm presented in this paper.     

A multi-objective modular design method for creating highly distinct independent modules

With the current rise in environmental concerns, customers want products that reduce environmental impacts. As a result, new multi-objective modular design methods are needed that can consider multiple design objectives, related to both the customers’ and the companies’ functional, environmental, and economical constraints and objectives. Most previous multi-objective modular design methods create module configurations, in which each module meets all of the design objectives. However, highly distinct independent modules are important for current product replacement processes. This paper presents an innovative multi-objective green modular design method that uses atomic theory and fuzzy clustering to create module configurations, in which each module meets one distinct design objective. This paper also presents case studies that demonstrate the capabilities of the new multi-objective green modular design method.     

Design of biorefinery systems for conversion of corn stover into biofuels using a biorefinery engineering framework

Unlocking the potential and value of lignocellulosic residues is an important step in making biorefineries economically and environmentally promising. This calls for a holistic and systematic approach in designing sustainable industrial systems. In this work, biorefinery systems via biochemical route (acetone–butanol–ethanol or ABE system) and thermochemical route (gasification and mixed alcohols or GMA system) for converting corn stover into biofuels have been designed using a Sustainable Engineering Framework. The framework involves eight main steps: (1) design problem definition, (2) data collection, (3) process synthesis and simulation, (4) process integration, (5) resource recovery from residues, (6) utility system design, (7) economic and environmental modelling and (8) economic value and environmental impact margin analysis for decision making. Consideration of resource recovery from biorefinery waste streams has proven to be the key in making biorefineries self-sustaining and with low environmental impacts. Simultaneous economic and environmental feasibility assessment at the early stage of process design is highly envisaged. The cost of biofuel production in the ABE system has been found to be 49.2 US$/GJ and 69.9 US$/GJ in the GMA system. The greenhouse gas emissions are 46.2 g CO₂-eq/GJ for ABE and 19.0 g CO₂-eq/GJ for GMA, lower than gasoline (85 g CO₂-eq/GJ). The GMA system is not economically compelling though with high environmental benefit, while the ABE system has shown to be both economically and environmentally feasible.     

Evaluating the environmental friendliness, economics and energy efficiency of chemical processes: heat integration

The design and improvement of chemical processes can be very challenging. The earlier energy conservation, process economics and environmental aspects are incorporated into the process development, the easier and less expensive it is to alter the process design. In this work different process design alternatives with increasing levels of energy integration are considered in combination with evaluations of the process economics and potential environmental impacts. The example studied is the hydrodealkylation (HDA) of toluene to produce benzene. This study examines the possible fugitive and open emissions from the HDA process, evaluates the potential environmental impacts and the process economics considering different process design alternatives. Results of this work show that there are tradeoffs in the evaluation of potential environmental impacts. As the level of energy integration increases process fugitive emissions increase while energy generation impacts decrease. Similar tradeoffs occur for economic evaluations, where the capital and operating costs associated with heat integration could be optimised. From the example designs considered here, an intermediate amount of energy integration produces the most economically beneficial and environmentally friendly process.     

Assessing the utility of environmental factors and objectives in environmental impact assessment practice: Western Australian insights

Environmental factors and objectives are formally identified during the scoping stage of environmental impact assessment (EIA) to structure and focus individual assessments. Environmental factors are broad components of the environment, while objectives set the desired outcome for a specific factor. This research assesses the utility of environmental factors and objectives in EIA practice based upon a combination of literature review and interviews with 21 EIA practitioners from Western Australia. Further to providing focus and structure for EIA, practitioners also use environmental factors and objectives for decision-making throughout the process. The majority of practitioners also note that factors and objectives are value adding and useful to their EIA practice. Due to their inherent subjective natures, interviewees noted a lack of consistency regarding how to meet the objectives and challenges in determining the significance of impacts on a factor. Identified opportunities to enhance use of objectives and factors in EIA included provision of more guidance, especially criteria or standards to apply and improve knowledge sharing between EIA stakeholders.     

Analysis of bioenergy production at different levels of integration in energy-driven biorefineries

In this paper, a techno-economic and environmental assessment is performed to compare the stand-alone process and biorefinery ways to produce biodiesel, ethanol and butanol as potential cases for bioenergy production using fresh fruit bunches as raw material. Different levels of integration are considered (e.g., mass and energy integration, non-conventional technologies) along with the analysis of the process scale to determine the economic profitability and environmental impacts of the proposed cases. The results demonstrated that the biodiesel production based on the biorefinery concept has a positive effect on the profitability of the stand-alone process at different scales. The economic results were compared with data reported in the literature. Furthermore, the life cycle analysis of the proposed cases suggested that the deployment of the biorefinery concept at different levels of integration in the oil palm supply chain reduced the environmental impact of the biodiesel production, which was selected as the hotspot of the evaluated cases.     

Process analysis and optimization of biodiesel production from soybean oil

The overall goal of this work is to design and optimize a biodiesel production process from soybean oil. To achieve this goal, several inter-connected activities were undertaken. First, an initial flowsheet for the process was synthesized. The performance of this flowsheet along with the key design and operating criteria were identified by conducting computer-aided simulation using ASPEN Plus. Various scenarios were simulated to provide sufficient understanding and insights and to select a base-case flowsheet. Next, mass and energy integration studies were performed to reduce the consumption of material and energy utilities, improve environmental impact, and enhance profitability. Capital cost estimation was carried out using the ICARUS Process Evaluator computer-aided tool linked to the results of the ASPEN Plus simulation. The operating cost of the process was estimated using the key information on process operation such as raw materials, utilities, and labor. A profitability analysis was carried out by examining the return on investment and the payback period. It was found that the cost of soybean oil is the largest contributor to the production cost. A sensitivity analysis was carried out to determine the effect of soybean oil prices on the process profitability.     

Selecting a near‐optimal design for multiple criteria with improved robustness to different user priorities

In a decision‐making process, relying on only one objective can often lead to oversimplified decisions that ignore important considerations. Incorporating multiple, and likely competing, objectives is critical for balancing trade‐offs on different aspects of performance. When multiple objectives are considered, it is often hard to make a precise decision on how to weight the different objectives when combining their performance for ranking and selecting designs. We show that there are situations when selecting a design with near‐optimality for a broad range of weight combinations of the criteria is a better test selection strategy compared with choosing a design that is strictly optimal under very restricted conditions. We propose a new design selection strategy that identifies several top‐ranked solutions across broad weight combinations using layered Pareto fronts and then selects the final design that offers the best robustness to different user priorities. This method involves identifying multiple leading solutions based on the primary objectives and comparing the alternatives using secondary objectives to make the final decision. We focus on the selection of screening designs because they are widely used both in industrial research, development, and operational testing. The method is illustrated with an example of selecting a single design from a catalog of designs of a fixed size. However, the method can be adapted to more general designed experiment selection problems that involve searching through a large design space.     

Sustainable manufacturing: a case study of the forklift painting process

Life cycle assessment (LCA) and design for environment (DFE) methods were applied to assess opportunities for reducing the environmental impacts of forklift manufacturing unit processes and to redesign those unit processes to increase overall sustainability. The unit processes of forklift manufacture generating the most environmental emissions were identified by applying LCA methodology. The results show that eco-toxicity and human toxicity were the most significant impacts of the forklift manufacturing process overall. Also, within the manufacturing unit processes, cutting, welding and painting had the highest impact values. In order to minimise environmental impacts, a new paint was created with increased solid content over the existing solvent paint used in the painting process. In addition, by applying DFE methodology and the high solid paint, overcoat and drying steps were eliminated from the forklift painting process. As a result, the environmental index of a follow-up LCA showed that environmental impacts could be reduced by 20%, while volatile organic compound (VOC) and paint usage could be decreased by 30% and 20%, respectively.     

An integrated approach to evaluating conceptual design alternatives in a new product development environment

As many companies have demonstrated over time, a conceptual design for a new product contributes greatly to an improvement in competitiveness, because it permits a reduction of costs, an increase in quality, and, often, a shortening of the time necessary to get the product on the market. That is why the evaluation of conceptual design alternatives created in a new product development (NPD) environment has long been very vital and a critical point for the future success of companies in fast-growing markets. These alternatives can be evaluated using the analytic hierarchy process (AHP), one of the most commonly used multiple criteria decision making (MCDM) techniques. This technique is used to reduce the number of conceptual design alternatives after ranking them using the scores obtained from the process. Furthermore, another technique, simulation analysis integrated with the AHP, is also used to help decision makers (product engineers or managers) perform economic analyses of the AHP's high-score alternatives using data from the generated simulation model of a real-life manufacturing system in which the final alternative is produced. In short, the objectives of this research are: first, to use the AHP technique to evaluate conceptual design alternatives in a NPD environment; second, to use a simulation generator integrated with this technique in order to perform economic analyses for the AHP's high-score alternatives. Finally, the results of both techniques, simulation and AHP, are used in a benefit/cost (B/C) analysis to reach a final decision on the conceptual design alternatives.     

A process systems framework for rapid generation of life cycle inventories for pollution control and sustainability evaluation

Life cycle assessment (LCA) is a tool that aids in sustainable decision-making among product and process alternatives. When implementing LCA, the efficient and accurate modeling of chemical processes for life cycle inventory (LCI) generation is still challenging. Challenges include a lack of systematic design and simulation tools and approaches to develop chemical process models for obtaining and analyzing more realistic LCI results. In this contribution, a novel process systems framework is proposed for estimating LCI results when implementing pollution control technologies. This framework involves the development and incorporation of pollution control unit (PCU) modules into process simulation and generation of LCI data associated with the PCUs for use in a sustainability evaluation. Different pollution control modules are designed for rapid LCI estimation and applied to obtain emissions, utility consumption, material, and land footprint results related to waste streams of a process simulation. Then, the LCI results are analyzed with the objectives of minimizing the environmental impact and utility consumption. The proposed framework is illustrated via a biomass/coal gasification process for syngas production with the end goal of acetic acid manufacturing. Results associated with this case study show that the developed framework can provide guidelines for sustainable decision-making based on generated LCI results.     

Environmental-impact reduction through simultaneous design, scheduling, and operation

Processing facilities are normally designed with sufficient flexibility to handle nominal variations. When the process features planned changes in feedstock and products, scheduling is often used to optimize process operation. Proper scheduling may be limited to existing design or may entail retrofitting. Traditionally, economic objectives have served as the primary drivers for the design, retrofitting, and scheduling of industrial processes. Once a base design and scheduling plan have been established, environmental issues are addressed in many cases as an afterthought. As a result of this sequential approach, valuable synergisms and tradeoffs of economic and environmental objectives are often missed. The objective of this study is to develop a new approach to design and scheduling with economic and environmental objectives. Specifically, this study introduces a systematic framework and the associated mathematical formulation for simultaneous process design and scheduling while simultaneously addressing economic and environmental objectives. Therefore, this study establishes two types of proper tradeoffs (a) between design and scheduling and (b) between economic and environmental objectives. The environmental issues pertaining to the parameterized process retrofitting, scheduling, and operation strategies are simultaneously considered along with the environmental impact of these changes. An optimization formulation is developed for the case of project schedule while allowing design retrofitting changes that include new environmental units and modification of design and operating conditions in the process (without new process units). Also, a process model with the appropriate level of relevant details is included in the formulation. The projected schedule is discretized to allow for a multiperiod formulation with algebraic equations. The resulting framework identifies opportunities for synergism between the economic and environmental objectives. It also determines points of diminishing return beyond which tradeoffs between economic and environmental objectives are established. The devised procedure is illustrated with a case study on an oil refinery with scheduling of different products and the design of an environmental system that addresses NO _x emission.     

Environmental and risk screening for prioritizing pollution prevention opportunities in the U.S. printed wiring board manufacturing industry

Modern manufacturing of printed wiring boards (PWBs) involves extensive use of various hazardous chemicals in different manufacturing steps such as board preparation, circuit design transfer, etching and plating processes. Two complementary environmental screening methods developed by the U.S. EPA, namely: (i) the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts (TRACI) and (ii) Risk-Screening Environmental Indicators (RSEI), are used to quantify geographic and chemical environmental impacts in the U.S. PWB manufacturing industry based on Toxics Release Inventory (TRI) data. Although the release weight percentages of industrial chemicals such as methanol, glycol ethers and dimethylformamide comprise the larger fraction of reported air and water emissions, results indicate that lead, copper and their compounds' releases correspond to the highest environmental impact from toxicity potentials and risk-screening scores. Combining these results with further knowledge of PWB manufacturing, select alternative chemical processes and materials for pollution prevention are discussed. Examples of effective pollution prevention options in the PWB industry include spent etchant recovery technologies, and process and material substitutions. In addition, geographic assessment of environmental burden highlights states where promotion of pollution prevention strategies and emissions regulations can have the greatest effect to curb the PWB industry's toxic release impacts.     

Optimization of multi-product batch plant design under uncertainty with environmental considerations

This paper presents a framework for the design and optimization of multi-product batch processes under uncertainty with environmental considerations. The uncertainties and environmental impacts are discussed. The profit and environmental impacts are considered as bi-objectives for batch plant design. The problem, thus, is formulated as a multi-objective stochastic programming problem. It can be converted into a single-objective two-stage stochastic linear programming problem using the weighted aggregation method. To solve the two-stage stochastic programming, we introduce both Monte Carlo sampling for the entire domain of the distribution function and the feasibility cut method based on dual theory in Benders’ decomposition. The detailed algorithm for problem-solving is presented. A numerical example is presented to illustrate the proposed framework.     

New procedure for optimal design of cogeneration system with considering environmental impacts and total cost

In this paper, a new procedure is introduced for optimal design of utility system in process industries. This method is based on the development of the R-curve concept and cogeneration targeting through estimating costs, environmental impacts, and exergoeconomic analysis. This new method can be applied for the synthesis of site utility system in process industries with considering total cost, environmental impacts, and exeregoeconomic analysis. In this regard, the powerful and accurate cogeneration targeting method is provided. The procedure which is proposed here provided a consistent, general procedure for determining mass flowrates and efficiencies of the applied turbines. Also, the new graphical representations are proposed. These curves can be easily constructed and simply understood. In addition, the optimal design of site utility is carried out in two case studies, in which the usefulness of this method is clearly demonstrated.     

Design of intelligent distributed control systems: a dependability point of view

The use of fieldbuses and the emergence of intelligent sensors and actuators are opening up new possibilities for distributed control systems, but are also introducing additional constraints in terms of achieving dependability objectives. The type of production environment will greatly determine the predominant criterion for an automatic control system, i.e. reliability, availability, maintainability, safety, etc. On the other hand, the choice of a fieldbus system will also depend on factors such as application size, data throughput, and integration of time considerations. Other important criteria include cost, confidentiality, and compatibility with existing equipment. Therefore, it appears essential that designers be given the means to assess dependability at each design step by integrating feedback from experience. Assessing dependability is too often limited to an evaluation at the end of the design process, which often involves reselecting previous choices. The main topic of this paper is to focus on the communication function which is a pivotal of intelligent distributed control systems. So this article is a synthesis of different aspects linked to the design of fieldbus based applications thanks to the contributors, who come from various fields. Consequently it highlights the main problem and give some ways to solve them.     

Coupled finite element simulation and optimization of single- and multi-stage sheet-forming processes

This article presents the development and application of a coupled finite element simulation and optimization framework that can be used for design and analysis of sheet-forming processes of varying complexity. The entire forming process from blank gripping and deep drawing to tool release and springback is modelled. The dies, holders, punch and workpiece are modelled with friction, temperature, holder force and punch speed controlled in the process simulation. Both single- and multi-stage sheet-forming processes are investigated. Process simulation is coupled with a nonlinear gradient-based optimization approach for optimizing single or multiple design objectives with imposed sheet-forming response constraints. A MATLAB program is developed and used for data-flow management between process simulation and optimization codes. Thinning, springback, damage and forming limit diagram are used to define failure in the forming process design optimization. Design sensitivity analysis and optimization results of the example problems are presented and discussed.