Rehan Sadiq

Life cycle iNdeX (LInX): a new indexing procedure for process and product design and decision-making

Life cycle assessment (LCA) is an important technique in the successful implementation of a process or product development in the context of environmental sustainability. Attempts have been made to incorporate LCA in public and corporate processes and product related decision-making. The European Union’s eco-labeling schemes and the United Kingdom’s Integrated Pollution Prevention and Control Directive have tried to integrate life cycle thinking with policy making. However, these efforts still have not made LCA an integral part of process and product selection and design. The absence of an easy to use tool for rapid reconnaissance is a basic limitation of the LCA application. A new life cycle indexing system — LInX — is proposed, which will facilitate the LCA application in process and product evaluation and decision-making. The LInX is comprised of four important sub-indices or attributes — environment, health and safety (EHS), cost, technical feasibility, and socio-political factors. Further, each attribute contains a number of basic parameters, e.g. EHS consists of 11 parameters. Quantification of each basic parameter is performed for the complete life cycle of a proposed process or product. An analytical hierarchy process is used to compute the weights for each basic parameter and sub-indices. A composite process is used to determine the final overall index. This paper explains the methodology for computation of the new indexing system and demonstrates it with an application.

Probabilistic risk analysis of corrosion associated failures in cast iron water mains

Abstract This paper proposes a method using probabilistic risk analysis for application to corrosion associated failures in grey cast iron water mains. External corrosion reduces the capacity of the pipeline to resist stresses. When external stresses exceed the residual ultimate strength, pipe breakage becomes imminent, and the overall reliability of a water distribution network is reduced. Modelling stresses and external corrosion acting on a pipe involves uncertainties inherent in the mechanistic/statistical models and their input parameters. Monte Carlo (MC) simulations were used to perform the probabilistic analysis. The reduction in the factor of safety (FOS) of water mains over time was computed, with a failure defined as a situation in which FOS becomes smaller than 1. The MC simulations yielded an empirical probability density function of time to failure, to which a lognormal distribution was fitted leading to the derivation of a failure hazard function. A sensitivity analysis revealed that the contribution of corrosion parameters to the variability of time to failure was more significant than the combined contributions of all other parameters. Areas where more research is needed are identified.

A review of multi-criteria decision-making methods for infrastructure management

In infrastructure management, multi-criteria decision-making (MCDM) has emerged as a decision support tool to integrate various technical information and stakeholder values. Different MCDM techniques and tools have been developed. This paper presents a comprehensive review on the application of MCDM literature in the field of infrastructure management. Approximately 300 published papers were identified that report MCDM applications in the field of infrastructure management during 1980–2012. The reviewed papers are classified into application to the type of infrastructure (e.g. bridges and pipes), and prevalent decision or intervention (e.g. repair and rehabilitate). In addition, the papers were also classified according to MCDM methods used in the analysis. The paper provides taxonomy of those articles and identifies trends and new developments in MCDM methods. The results suggest that there is a significant growth in MCDM applications in infrastructure management applications of MCDM over the last decade. It has also been noted that many decision support tools based on multiple MCDM methods have been successfully used for infrastructure management.

Evidential cognitive maps

In order to handle uncertain information, this paper proposes evidential cognitive maps (ECMs), similar to the fuzzy cognitive maps (FCMs). ECMs are uncertain-graph structures for representing causal reasoning through the combination of cognitive maps and Dempster Shafer evidence theory. The framework of ECMs is developed in detail and an application to socio-economic model is used to illustrate the application of the proposed methodology.

A fuzzy-based methodology for an aggregative environmental risk assessment: a case study of drilling waste

The objective of this study was to develop a methodology for estimating aggregative risk of various environmental activities, pollution sources and routes in a given process. The rate of risk is defined by a product of grade of risk (r, magnitude) and grade of importance (i, intensity). Both factors r and i are expressed by an 11-level qualitative scale which are defined by triangular fuzzy numbers to capture the vagueness in the linguistic variables. A three-stage hierarchical structure aggregative risk model was developed for grouping of risk items. For this grouping an analytical hierarchy process was used. A sensitivity analysis was also performed to verify the effect of weighting schemes on the assessment of a final aggregative risk. The developed methodology is applied to a case study of offshore drilling waste for evaluating various discharge scenarios.

Fault and Event Tree Analyses for Process Systems Risk Analysis: Uncertainty Handling Formulations

Quantitative risk analysis (QRA) is a systematic approach for evaluating likelihood, consequences, and risk of adverse events. QRA based on event (ETA) and fault tree analyses (FTA) employs two basic assumptions. The first assumption is related to likelihood values of input events, and the second assumption is regarding interdependence among the events (for ETA) or basic events (for FTA). Traditionally, FTA and ETA both use crisp probabilities; however, to deal with uncertainties, the probability distributions of input event likelihoods are assumed. These probability distributions are often hard to come by and even if available, they are subject to incompleteness (partial ignorance) and imprecision. Furthermore, both FTA and ETA assume that events (or basic events) are independent. In practice, these two assumptions are often unrealistic. This article focuses on handling uncertainty in a QRA framework of a process system. Fuzzy set theory and evidence theory are used to describe the uncertainties in the input event likelihoods. A method based on a dependency coefficient is used to express interdependencies of events (or basic events) in ETA and FTA. To demonstrate the approach, two case studies are discussed.

Probability density functions based weights for ordered weighted averaging (OWA) operators: An example of water quality indices

Abstract This paper explores the application of ordered weighted averaging (OWA) operators to develop water quality index, which incorporates an attitudinal dimension in the aggregation process. The major thrust behind selecting the OWA operator for aggregation of multi-criteria is its capability to encompass a range of operators bounded between minimum and maximum . A new approach for generating OWA weight distributions using probability density functions (PDFs) is proposed in this paper. The basic parameters (mean and standard deviation) of the probability density functions can be determined using the number of criteria (e.g., water quality indicators) in the aggregation process. The proposed approach is demonstrated using data provided in a study by Swamee and Tyagi [Swamee, P.K., Tyagi, A., 2000. Describing water quality with aggregate index. ASCE Journal of Environmental Engineering 126 (5), 451–455] for establishing water quality indices. The Normal distribution and its inverse form were found suitable for compromising or normative decisions, whereas the Exponential and its inverse form were found suitable for pro-risk and risk-averse decisions, respectively. The proposed OWA weight distributions are also compared with the commonly used regular increasing monotone (RIM) functions for generating OWA weights. Sensitivity analyses are carried out to highlight the utility of the proposed approach for multi-criteria decision-making and establishing water quality indices.

GreenPro-I: a risk-based life cycle assessment and decision-making methodology for process plant design

Abstract In recent years, significant attention and emphasis has been given to cleaner and greener technologies in processes and product manufacturing. This is recognized as a key element in pollution prevention (P2) and development of sustainable strategies. Life cycle assessment (LCA) is a systematic approach that enables implementation of cleaner and greener product and process concepts in industry. In recent times substantial progress has been made in the use of LCA for product evaluation and selection. However, its use in cleaner and greener process design and decision-making has not been explored to a great extent. Process design and decision-making are challenging activities that involve trade-off of conflicting objectives, namely costs, technical feasibility and environmental impacts. These conflicting objectives can be analysed at the early design and decision-making stage by considering the full life cycle of a process or a product. A cleaner and greener process is the one that is cost optimal, technically feasible, and environmentally benign. To obtain these results LCA requires various tools and techniques in a systematic methodology. This paper proposes a holistic and integrated methodology GreenPro-I for process/product design by combining the traditional LCA approach with multi-criteria decision-making methods. This methodology is simple and applicable at the early design stage and is more robust against uncertainty in the data. Application of the methodology has been demonstrated in the paper through a urea production case study.

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review

Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, and finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies.

Risk-based process safety assessment and control measures design for offshore process facilities

Process operation is the most hazardous activity next to the transportation and drilling operation on an offshore oil and gas (OOG) platform. Past experiences of onshore and offshore oil and gas activities have revealed that a small mis-happening in the process operation might escalate to a catastrophe. This is of especial concern in the OOG platform due to the limited space and compact geometry of the process area, less ventilation, and difficult escape routes. On an OOG platform, each extra control measure, which is implemented, not only occupies space on the platform and increases congestion but also adds extra load to the platform. Eventualities in the OOG platform process operation can be avoided through incorporating the appropriate control measures at the early design stage. In this paper, the authors describe a methodology for risk-based process safety decision making for OOG activities. The methodology is applied to various offshore process units, that is, the compressor, separators, flash drum and driers of an OOG platform. Based on the risk potential, appropriate safety measures are designed for each unit. This paper also illustrates that implementation of the designed safety measures reduces the high Fatal accident rate (FAR) values to an acceptable level.