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The purpose of this paper is to show how technical-economical cost modeling can help in steering research and development to target key production cost elements of new products based on emerging technologies.

The authors demonstrate the development and use of a technical-economic cost model (TCM) of the proton exchange membrane (PEM) in fuel cells to steer research to produce more economical and reliable products. A TCM is developed to depict how the production cost per unit varies depending on the different fabrication methods, production rate limitations, material selection, labor distribution, energy consumption, financial parameters and the target production volume. By using such an approach in the design, research time and resources can be saved by prioritizing R&D and production scale-up options at an early stage.

The results of this study show the importance of applying technical-economic cost model (TCM) techniques on early stage research projects to steer the development for resolving key problematic figures. As a case study, a cost analysis platform has been established to apply this technique by analyzing different manufacturing and R&D options for producing durable PEM fuel cells. The projected manufacturing cost of the PEM is found to be lower than previously estimated and the enhanced durability does not significantly impact this production cost.

Production is an important factor in informing NPD targets and R&D direction. And yet it is difficult to estimate scaled up production cost for prototype products and components in the R&D lab. Technical-economic cost models (TCM) are a tool to assist decision-making in technology portfolio management and NPD.

This extended editorial viewpoint aims to introduce the individual contributions for this special issue.

The articles included in this special issue are reviewed.

The preliminary synthesis of all articles identifies four different perspectives on this topical area: a corporate strategy perspective, a cross-functional work-process perspective, an outsourcing perspective and a specific Chinese perspective.

Some of the articles in this special issue are of a theoretical character; thus, further empirical research is recommended.

The individual papers present important information, guidelines and frameworks that firms can use in their efforts to bridge the manufacturing – R&D interface.

This special issue focuses on a less-researched topical area and attempts to bridge the disciplines of operations and innovation management.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

This paper aims to deal with a real-life strategic conflict in joint operations (JOs) for facility location decision and planning in an oil and gas field that stretches over two countries and tries to develop a basis for mitigating such conflict.

This paper develops a novel approach using integer linear programming (ILP) to determine optimal facility location considering technical, economic and environmental factors. Strategic decision-making in JOs is also influenced by business priorities of individual partner, sociopolitical issues and other covert factors. The cost-related quantitative factors are normalized using inverse normalization function as these are to be minimized, and qualitative factors that are multi-decision-making criteria are maximized, thus transforming both qualitative and quantitative factors as a single objective of maximization in ILP model.

The model identifies the most suitable facility location based on a wide range of factors that would provide maximum benefit in the long term, which will help decision-makers and managers.

The model can be expanded incorporating other quantitative and qualitative factors such as tax incentives by the government, local bodies and government regulations.

The applicability of the model is not limited to JOs or oil/gas field, but is applicable to a wide range of sectors.

The model is transparent and based on rational and scientific basis, which would help in building consensus among the dissenting parties and aid in mitigating strategic conflict. Such type of model for mitigating strategic conflict has not been reported/used before.

The main objective of safety instrumented systems (SISs) is to maintain a safe condition of a facility if hazardous events occur. However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).

The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).

A case study concerning a safety instrumented system implemented in the RGTE facility has shown the great applicability of the proposed approach and the results are encouraging. The results show that the selection of a good maintenance strategy allows a very significant minimization of the PFDavg, the frequency of spurious trips and Life Cycle Costs of SIS.

The maintenance strategy defined by the system designer can be modified and improved during the operational phase, in particular safety systems. It constitutes one of the least expensive investment strategies for improving SIS performances. It has allowed a considerable minimization of the SIS life cycle costs; PFDavg and the frequency of spurious trips.

The USA is one of the largest oil producers in the world. For this purpose, the authors model and predict the US conventional and unconventional oil production during the period 2000–2030.

In this research, the system dynamics (SD) model has been used. In this model, economic, technical, geopolitical, learning-by-doing and environmental (social costs of carbon) issues are considered.

The results of the simulation, after successfully passing the validation test, show that the US unconventional oil production rate under the optimistic scenario (high oil prices) in 2030 is about 12.62 million barrels/day (mb/day), under the medium oil price scenario is about 11.4 mb/day and under the pessimistic scenario (low oil price) is about 10.18 mb/day. The results of US conventional oil production forecasting under these three scenarios (high, medium and low oil prices) show oil production of 4.62, 4.26 and 3.91 mb/day, respectively.

The contribution of this study is important in several respects: First, by modeling SD that technical, economic, proven reserves and technology factors are considered, this paper models US conventional and unconventional oil production separately. In this modeling, nonlinear relationships and feedback loops are presented to better understand the relationships between variables. Second, given the importance of environmental issues, the modeling of social costs of CO₂ emissions per barrel of oil is also presented and considered as a part of oil production costs. Third, conventional and unconventional US oil production by 2030 is forecast separately, the results of this study could help policymakers to develop unconventional oil and plan for energy self-sufficiency.

This article is based on the REACCESS research project, sponsored by the European Commission, with the objectives of evaluating the technical, economic, and environmental aspects of present and future energy corridors between the European countries (EU27) and their main energy suppliers. GCC countries have an important role to play given their role in EU energy supply and in greenhouse gas emissions. The paper aims to discuss these issues.

A single energy model was built by hard‐linking the TIMES integrated assessment model (TIAM‐World), the Pan European TIMES model (PET), and the RECOR model (REaccess CORridors), including more than 1,000 possible energy corridors supplying the European countries. Another major methodology advance was to create a hybrid objective function, combining the usual cost objective and a metric representing the supply risk incurred by EU27. The risk component was constructed via a novel approach that aggregates the elemental risk parameters of each corridor using a Min‐Max function. Four contrasted scenarios were assessed, based on security and climate objectives.

Among the many results, it appears that a large reduction of the supply risk may be achieved at a very modest increase of the total energy system cost for EU27. Cross‐effects of climate mitigation and security objectives are also observed. Due to the diversification requirement, the contribution of GCC countries to EU energy imports increases under risk scenario. Sensitivity analyses show that the European energy system seems unable to reduce the market shares of fossil fuels import from MENA countries, including GCC countries, much below the reference case, proving the strong dependency of EU27 energy system from these countries. However, total fossil fuels imports, as well as total energy consumed, are decreased under the risk adverse scenarios.

Methodological developments, as described above, result in an advanced tool to assess how to increase the “energy system security”, by reducing the concentration of supply countries, diversifying import sources but also reducing the energy dependence at the end‐use side.

The inherent risks and their interactive impacts in megaproject development have been found in numerous cases worldwide. Although risk management standards have been recommended for the best practice in engineering construction projects, there is still a lack of systematic approaches to describing the interactions. Interactions such as social, technical, economic, ecological and political (STEEP) risks have complex and dynamic implications for megaproject construction. For a better understanding and effective management of megaprojects such as the Edinburgh Tram project, the dynamic interaction of concomitant risks must be studied.

A systems dynamic methodology was adopted following the comprehensive literature review. Documentary data were gathered from the case study on Tram Network Project in Edinburgh.

A casual loop of typical evolution of key indicators of risks was then developed. A hypothesised model of social and ecological (SE) risks was derived using the system dynamics (SD) modelling technique. The model was set up following British Standards on risk management to provide a generic tool for risk management in megaproject development. The study reveals that cost and time overruns at the developmental stage of the case project are caused mainly by the effects of interactions of risk factors from the external macro project environment on a timely basis.

This article presented a model for simulating the socio-ecological risk confronting the management and construction of megaprojects. The use of SD provided the opportunity to explain the nature of all risks, particularly the SE risks in the past stages of project development.

The purpose of this paper is to propose a new multi-criteria decision making (MCDM) technique to determine the priority of renewable power plants construction conceding technical, economic, social, political and environmental aspects.

First, a comprehensive set of 5 main criteria of technical, economic, social, political and environmental are considered for renewable power plants construction, each including 5 sub-criteria (a total of 25 sub-criteria). Then, the analytic hierarchy process method is used to determine the weight of the criteria. Finally, a new MCDM technique proposed to prioritize the construction of renewable power plants, named TOPKOR. To demonstrate the capability of the proposed method, a case study is conducted in which six types of renewable power plants are evaluated.

Comparison results of the main criteria weights show that the “economic” [0.403], “environmental” [0.296] and “technical” [0.17] aspects have the highest importance, respectively. The results also show that solar, hydroelectric and wave and tidal power plants have the highest priority for construction, respectively.

The result of this research could be useful for related decision makers in construction of the renewable power plants to have a comprehensive set of criteria in technical, economic, social, political and environmental aspects in their decision process.

This research provides a comprehensive set of criteria and sub-criteria for prioritizing the renewable power plants. Moreover, a new hybrid MCDM technique is introduced for prioritizing the construction of power plants.

The purpose of the article is to identify relevant criteria for decision support in the implementation of waste-to-energy (WtE)-based systems.

The methodology is a simple case study with a qualitative approach. Five experts involved in the project of a thermoelectric power plant qualitatively evaluated, on a Likert scale, a decision model with 15 indicators derived from recent studies. The research object was the first stage of a project to implement a thermoelectric plant employing municipal solid waste (MSW) in southern Brazil.

The study identified 15 criteria supporting the decision-making process regarding WtE implementation for MSW in a mid-sized city in southern Brazil. The study identified that compliance with MSW legislation, compliance with energy legislation, initial investment and public health impact are the most influential criteria. The study offered two models for decision processes: a simplified one and a complete one, with ten and fifteen indicators, respectively.

The study concerns mid-sized municipalities in southern Brazil.

Municipal public managers have now a methodology based on qualitative evaluation that admits multiple perspectives, such as technical, economic, environmental and social, to support decision-making processes on WtE technologies for MSW.

MSW management initiatives can yield jobs and revenues for vulnerable populations and provide a correct destination for MSW, mainly in developing countries.

The main originality is that now municipal public decision-makers have a structured model based on four constructs (technical, economic, environmental and social) deployed in 15 indicators to support decision-making processes involving WtE and MSW management.