Sustainability Modeling in Engineering

The following sections are included:

• Dedication
• Preface
• About the Editors
• About the Contributors
• Acknowledgments
• Contents

Logistics and transportation are necessary for modern communities for mobility. Rising population, growing economy and increasing transactions, attractive tourism industry and unpredictable technological change push the regional and provincial governments to put in place an advanced logistics system that fits the society. At present, in big urban regions, locating a logistics and distribution center is drawing considerable attention. The location of strategic logistics centers (LCs) is likely to receive extra focus in the coming years because of global mobility, economic competitiveness and unwanted immigration all over the world. How to deal with that situation is on top of the mind of an executive manager who is charged with decision making. Policymakers at the highest levels of the decision-making pyramid always resort to analytical solutions, guidelines, and a systematic approach.

Multi-attribute decision-making (MADM) refers to a class of decision-making techniques based on which several alternatives are evaluated with respect to a number of criteria. The criteria are defined as either quantitative or qualitative. The objective of this study is to establish a LC and find the best location for Andalucía government in Spain. The question is how the optimal location of LCs can be found in order to facilitate logistics and transport demands in response to increasing growth in industry and tourism. In relation to this problem, a research group evaluated a series of alternatives to get possible solutions.

In petroleum refinery projects (PRPs) various engineering disciplines are involved; also, many types of stakeholders are dealt with such as vendors and governments. Therefore, PRPs are complex and multi-disciplinary; and in order to assess the sustainability of these projects in each and all of the triple bottom lines (economic, social and environmental), an integrated framework and a comprehensive approach is needed. To assess the sustainability of PRP vis-à-vis each pillar, many criteria will be defined.

In this chapter, life-cycle model of PRP will be introduced and used as a basis for developing sustainability assessment tools based on multiple-criteria decision-making (MCDM) techniques in combination with green construction assessment methodologies.

A set of sustainability indicators and factors are defined at first as a representation of sustainability pillars. The gist of the assessment tool is a normalized summation of sustainability factors in different life-cycle phases. However, the framework needs to be dynamic to adapt to the continuous changes in the PRP. It is important to note that the dynamic methodology would be more ambiguous than its static counterpart. In this chapter, the dynamic methodology is defined at different levels of decision-making, with crisp, gray and fuzzy numbers as required.

Both decision-making or policymaking and regulatory measures have an undeniable role in directing and leading a community, society or a country. New methods and tools are being developed to ensure a brighter future because our future hinges on our current decisions. Prospective multiple-attribute decision-making (PMADM) as a new approach in multiple-attribute decision-making (MADM) structure has been developed as a powerful tool for making critical decisions and policies. PMADM as an approach with a flexible structure or a pilot for developing policies and making decisions can cover more uncertainties and ambiguities in real situations. The government, regulatory bodies, policymakers and organizations are in constant endeavor to apply the best policies and decisions in their activities and responsibilities.

The Iranian National Medical Device Directorate is a regulator of the medical device industry of Iran. This organization considers ensuring a sustainable future (critical aspects of sustainability) by managing the present conditions, which is the main aim of this study. Iran is planning to increase the share of medical device market ten times more as a sustainable market for the country. For this aim, the PMADM approach was adopted as a pilot for the policymaking procedure. Max capacity, ideal directed scenario and supportive backup criteria are presented as the new approaches for applying the PMADM structure. Supportive backup criteria open a new window for illustrating different scenarios and vision in response to a complicated future. In the end, the directorate and policymakers are concerned with how is it possible to see uncertainties of the future in deeper scenarios and challenges. As an example and a pilot, this study can open up new horizons for similar studies in the future.

A sustainable agricultural practice (SAP) is vital to preserving the environment, and at the same time, this practice would increase agricultural productivity. The importance of SAP and its indicators is indisputable. However, the importance of one indicator over other indicators of sustainable agriculture is not conclusive. Moreover, the multiple indicators of environment, economic and social aspects of agriculture sustainability are vague and interrelated. This research aims to investigate the interdependence among indicators that would affect the SAP. Ten indicators of SAP are selected and analyzed using the integration of intuitionistic fuzzy sets (IFS) and decision-making trial and evaluation laboratory (DEMATEL) method. The IFS-DEMATEL method is known as an effective tool to investigate the interrelationships among indicators via a causal diagram and digraph. Unlike fuzzy DEMATEL, the proposed IFSDEMATEL used a centroid method to defuzzify membership, nonmembership and hesitancy values of IFS into a single crisp score. The causal diagram reveals that five indicators are classified as the cause group while five other indicators are classified as the effect group. The highest value of (D + R) indicates that “cultivation” is the most important indicator of agriculture sustainability. The findings of this study could provide a valuable reference for developing policies related to SAP.

As in many developing countries, Libya is still inappropriately managing the solid waste. This has led to increase the amount of solid waste accumulated in the country. The objective of this study is to select an appropriate waste management technology for Libya. However, the selection of an appropriate waste management technology is a complex process, because it is necessary to consider a wide range of parameters. Best available techniques, technology quality method and multicriteria analysis were proposed as means of developing indices for evaluating municipal waste management systems. In this work, four treatment systems for waste management in Libya are evaluated using fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) in respect to four main criteria and 22 subcriteria. The treatment systems for waste management are anaerobic digestion, landfilling, incineration and compost. The selected criteria used in the evaluation of four treatment systems are environmental impacts, socio-cultural aspects, technical aspects and economic aspects. According to the evaluation, anaerobic digestion (AD) ranks the highest in classification in Libya. Compost ranks higher than landfilling and incineration. Sensitivity analysis, which consists of 20 different scenarios, shows that the proposed model is very stable. Furthermore, it should be noted that the rank of waste treatment systems can be changed according to the future technological developments.

Waste management is important as well as challenging for humankind and many market segments. It is linked to diverse worldwide challenges, like health, climate change, poverty alleviation, food and resource security, and sustainable manufacturing and utilization. The sustainable development objective for an organization cannot be achieved without addressing waste management as a priority. Therefore, waste disposal in an accountable, secure and principled manner is enormously significant for waste management. Moreover, efficient waste management system benefits an enterprise through cost savings and promoting environment-friendly practices. India faces foremost ecological threats related to waste generation and derisory waste collection, transport, handling and dumping. Existing systems in India can barely effectively deal with the amount of waste generated by a growing metropolitan populace. The challenges and blockade are noteworthy, but so are the prospects. Hence, it is imperative to understand the key performance drivers of waste disposal management system of a municipality. Balanced Scorecard (BSC) model is a modern strategic management technique that can help managers to identify an organization’s Key Performance Indicators (KPIs) on four interrelated perspectives, i.e., financial, customer, internal business processes and learning and growth. Therefore, this chapter first develops a BSC model for a Municipal Corporation in India to facilitate enterprise view of an organization’s overall performance to the policymakers. Next, a framework based on Analytical Hierarchy Process (AHP) method is designed to measure the performance of the Municipal Corporation over a period of time with respect to KPIs in the BSC model in order to validate the efficacy of strategies employed.

In the manufacturing industry, productivity modeling can be used as an essential tool for predicting future productivity and allocating optimal resources for production. This chapter introduces a rough number set method into a hierarchy manufacturing model to establish a typical productivity model. Rough number set describes a range of uncertain criteria weight. By implementing this method, the criteria in each level of an analytic hierarchy process (AHP) model can be defined with an array with the same space instead of a precise number. After multiplying the rough number sets, the relative global weight of each parameter can be calculated. With this method, a productivity model can be established with imprecise input. This model responds with a predictable change of overall productivity with the change of imprecise input.

This investigation aims to predict the optimal machining conditions in abrasive assisted electrical discharge machining (EDM) of Ti-based biomaterial. The present study focuses on tool erosion rate (TER), material erosion rate (MER) and surface roughness (SR) analysis of titanium (Ti–6Al–4V)-based biomaterial in SiC-mixed hybrid ED machining. Copper electrodes with a variable inner hole diameter were selected while machining in SiC_p mixed dielectric medium. The output was globally optimized by desirability function technique to predict the suitable parametric combinations for the selected workpiece machining. This machining route revealed a considerable enhancement in MER and SR in abrasive-mixed dielectric fluid. In this dielectric flushing method, a considerable decline in tool wear affected by peak current while using SiC particulates was observed. Subsequently, SR was predominantly enhanced under the influence of hole size, pulse-off and abrasive mixed dielectric as the control parameters. The scanning electron micrographs revealed vital influence pertaining pulse-on duration, peak current and type of dielectric fluid on the microstructure of machined surfaced of Ti–6Al–4V samples. In a nutshell, the use of novel hybrid machining route and the optimization technique of experimentation proved to be beneficial in preserving product quality and manufacturing equipment, which can be a source for additional environmental sustainability and process costs.

Cell formation and production planning are two important steps in implementing the group technology system. In this research, the use of multiattribute decision-making concepts and similarity coding system is suggested in designing components to create a cellular model. An improved algorithm with rank order clustering (ROC) and row and column masking (RCM) methods was proposed for application in Parizan Sanat Co. as a case study. The results were compared to the productivity index, and the superiority of the improved algorithm was observed compared to the previous methods.

The chapter presents the advances in microelectrical discharge machining process with various dielectrics used during micromachining so as to improve the machining performance. Microelectrical discharge machining is an established method and has a huge demand in the manufacturing sector in addition to its appeal among the researchers for exploring its potential so as to produce microfeatures with higher precision, accuracy and surface integrity. The dielectric fluid employed in the micro-EDM process plays a major function for achieving the desired features. Therefore, it is important to understand its role in micro-EDM machining. The chapter attempts to review the gradual evolution of micro-EDM machining with different dielectrics and their effects on the variety of performance measures such as machining rate, rate of tool wear and geometric accuracy and the sequential development that has taken place over the years on the use of dielectrics during micromachining of various conducting materials.

This chapter presents the implementation of a new multicriteria group decision-making (MCGDM) model; this is based on intuitionistic fuzzy technique for order of preference by similarity to ideal solution (IFTOPSIS) method, dynamic intuitionistic fuzzy Einstein geometric averaging (DIFWGϵ) operator and intuitionistic fuzzy entropy (IFE) method for the selection of a sustainable power transformer design concepts under a dynamic environment. The model, which addresses the dynamic issues in the development of new products, also contributes to the sustainable design study by accounting for the uncertainty in the decision-making process. To the best of my knowledge, this is the first study to select sustainable design concepts under a dynamic environment or consider the dynamic issues in the development of a new product while meeting sustainability goal.

In Indonesia, which has the largest archipelago in the world, most coastal and small island regions in the country rely upon their daily economic activities in fisheries and marine resource utilization, including seaweed cultivation. Some of the regions are still entirely situated in remote areas such as Kei Islands in Maluku Province, which have relatively smallest islands in the region lacking in infrastructure. The location of these islands brings a whole new challenge for maintaining not only an ideal interisland supply chain but also transportation within the islands. Kei Islands is one of the leading producers of seaweed from eastern Indonesia and therefore reducing the risks of seaweed supply chain within and outside these islands has become a necessity to sustain productivity of seaweed. In this chapter, an integrated multicriteria decision-making (MCDM) with fuzzy logic is used to provide a better decision based on a large number of related complex factors. House of risk (HOR) is performed in the MCDM tool, which was developed based on quality function deployment (QFD) and FMEA concept, and fuzzy AHP to provide a better understanding and give the best alternative to minimize the risks encountered in the seaweed supply chain on the intra-island and inter-island regions in Kei Islands, Indonesia.

The main aim of the decision-makers in a deregulated power market is to maximize their profits and reduce their risks. The profit of private companies is affected by several parameters as well as uncertainties in the deregulated power market. These uncertain parameters also include the strategic behavior of rivals and regulatory interventions. Therefore, in order to reduce risks and increase profits, private companies as decision-makers in the deregulated power market should consider all parameters in their planning. In this chapter, a mathematical model has been developed to determine the market clearing price (MCP) in each season and load levels as well as the profit of each private firm by considering on-ground realities such as bilateral contracts, carbon tax and the rational uncertainty in the deregulated power market. Using this mathematical model, private companies in the deregulated power market can predict the generation strategies of other investors. The proposed framework has been implemented in the hypothetical deregulated power market by using the IEEE reliability test system. The case study chosen in this research has confirmed that this model provides robust decisions and precise information about the deregulated power market.

Smog refers to air pollution caused due to industrial and anthropogenic emissions. It increases opacity and toxicity of air. It produces a challenging situation around the world, causing increase in road accidents, crop damage, health risks, disruptions in industry cycle and halting daily life routine in many big and small cities around the globe. This chapter illustrates an extensive research and analysis of facts and data for various causes of smog around the world, with a special focus on Pakistan. Lahore, the second largest city of Pakistan, is one of the most smog-affected zones. The biggest causes of smog are agricultural fires and hazardous emissions from industries and automobiles. To avoid smog formation due to these causes, different alternative solutions are developed. A framework based on fuzzy-VIKOR MCDM approach is used to select the best alternative solution. Agricultural fire can be avoided by using mechanical and chemical means to destroy the residue. Emissions from the industry and automobiles can be reduced by using modern technology and making new regulations. In the last part of this chapter, recommendations are proposed to facilitate the government in making of strategies to counter smog and regulation of laws in this regard by checking severity of different causes.

Energy is vital for the world economy. The expanding need for energy because of industrialization, population explosion and the increase in ordinary comforts has prompted a huge utilization of petroleum derivatives. Biodiesel seems to be a respectable option among petroleum-based fuels. In any case, the suitability of biodiesel is the main criterion for figuring out it as a substitute fuel for internal combustion (IC) engines. Affordable biodiesel with a proper combination for the IC engine assumes significance due to emissions from petroleum-based fuels. The intention of this research is to choose the best suitable fuel blends using analytical hierarchical process (AHP) and multiobjective optimization on simple ratio analysis (MOOSRA) methods. The AHP method is applied to discover the relative weights of the standards, even as a MOOSRA has been applied to distinguish the first-class alternatives. Experimental results from HC, NO_x, CO, EGT, CO₂ and BTE have been considered because of the assessment standards. From the results, it is seen that B20 is the best combination to be used in IC engines.

This chapter presents an application of analytic hierarchy process (AHP) for the selection of renewable energy sources (RESs) and technology for developing countries with moderate climatic conditions. The commonly available renewable sources like solar, wind, hydroelectric, geothermal, biomass and ocean have been considered for evaluation based on different criteria. The importance weights of the criteria and subcriteria as well as preferential ranking of options have been determined by eliciting expert judgment through pairwise comparisons. The assessments show that within the technological constraints, hydro energy is the most preferred option, followed by solar and then wind energy in developing countries. However, as time progresses and technology improves, the preferential ranking might change. Moreover, the implications of ranking vary with geographical locations.

The following section is included:

• Index