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The purpose of this paper is to develop a risk evaluation method for the industrial network under high uncertain environment.

This paper introduces an extended safety and critical effect analysis (SCEA) method, which takes the weight of each industry in a network into risk assessment. Furthermore, expert experience and fuzzy logic are introduced for the evaluation of other parameters.

The proposed approach not only develops weight as the fifth parameter in quantitative risk assessment but also applies the interval type-2 fuzzy sets to depict the uncertainty in the risk evaluation process. The risk rating of each parameter excluding weight is determined by using the interval type-2 fuzzy numbers. The risk magnitude of each industry in the network is quantified by the extended SCEA method.

There is less study in quantitative risk assessment in the industrial network. Additionally, fuzzy logic and expert experience are expressed in the presented approach. Moreover, different parameters can be determined by different weights in network risk assessment in the future study.

The extended SCEA method presents a new way to measure risk magnitude for industrial networks. The industrial network is developed in risk quantification by assessing weights of nodes as a parameter into the extended SCEA. The interval type-2 fuzzy number is introduced to model the uncertainty of risk assessment and to express the risk evaluation information from experts.

The purpose of this paper is to investigate the internationalisation of enterprises by specific forms of foreign direct investments (FDI) and international technical cooperation in the defence sector.

The effects of defence FDI and international technical cooperation activities on the Slovenian economy are investigated using the input‐output modelling approach.

The author finds important direct and indirect effects on the Slovenian economy from the FDI and international technical cooperation inflows into enterprises. These positive effects are directly and indirectly linked to enterprises in different statistically classified industrial activities by predominance of the civil sector, which is important for the development of defence and civilian high‐technological base products in different regional parts of Slovenia.

The presented findings can be used to arrange industrial and regional development strategy and policy measures aimed at accelerating the internationalisation of enterprises and different industrial activities.

Delineating where stability occurs in a contract provides the window of opportunity for procurement officials to positively affect cost and schedule outcomes. While the concept of a Cost Performance Index (CPI) "stability rule" has been routinely cited by Earned Value Management (EVM) authors since the early 1990's, more recent research questions the veracity of this stability rule. This paper resolves the controversy by demonstrating that the definition of stability matters. We find a morphing of the stability definition over time, with three separate definitions permeating the literature. Next, an analysis of Department of Defense contracts for both cost and schedule stability properties finds that the veracity of the stability rule is intricately tied to the definition used.

In the light of challenges experienced in cost estimation at the bidding stage of complex engineering services in the defence industry (e.g. contracting for availability), the purpose of this paper is to present a framework to manage the influence of uncertainty on cost estimates.

The research applied the Soft Systems Methodology and benefitted from interaction with four major organisations in the defence industry through document sharing, semi-structured interviews, workshops, and case studies.

The framework is composed of seven stages to plan, identify, prioritise, classify, and manage cost uncertainties. Through the validation of three case studies some of the key benefits of the framework were realised in project planning, uncertainty visualisation, and capability management.

The research has been applied in the defence sector in the UK and focuses on the bidding stage. Further research needs to be applied to confirm that the findings are applicable across industries and across the life cycle.

The paper builds on the theory behind risk and uncertainty management and proposes an innovative framework that avoids the assumption of “perfect” knowledge by raising questions about the validity of the input data.

Cost estimation is one of the most significant steps in construction planning, which must be undertaken in the preliminary stages of any project; it is required for all projects to establish the project's budget. Confidence in these initial estimates is low, primarily due to the limited availability of suitable data, which leads the construction projects to frequently end up over budget. This paper investigated the efficacy of artificial neural networks (ANNs) methodologies in overcoming cost estimation problems in the early phases of the building design process.

Cost and design data from 104 projects constructed over the past five years in Jordan were used to develop, train and test ANN models. At the detailed design stage, 53 design factors were utilized to develop the first ANN model; then the factors were reduced to 41 and were utilized to develop the second predictive model at the schematic design stage. Finally, 27 design factors available at the concept design stage were utilized for the third ANN model.

The models achieved average cost estimation accuracy of 98, 98 and 97% in the detailed, schematic and concept design stages, respectively.

This paper formulated the aims and objectives to be applicable only in Jordan using historical data of building projects.

The ANN approach introduced as a management tool is expected to provide the stakeholders in the engineering business with an indispensable tool for predicting the cost with limited data at the early stages of construction projects.

This paper proposes an integrated IT2F-FMEA model under a group decision-making setting. In risk assessment models, experts' evaluations are often aggregated beforehand, and necessary computations are performed, which in turn, may cause a loss of information and valuable individual opinions. The proposed integrated IT2F-FMEA model aims to calculate risk priority numbers from the experts' evaluations and then fuse experts' judgments using a novel integrated model.

This paper presents a novel failure mode and effect analysis (FMEA) model by integrating the fuzzy inference system, best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) methods under interval type-2 fuzzy (IT2F) environment. The proposed FMEA approach utilizes the Mamdani-type IT2F inference system to calculate risk priority numbers. The individual FMEA results are combined by using integrated IT2F-BWM and IT2F-WASPAS methods.

The proposed model is implemented in a real-life case study in the furniture industry. According to the case study, fifteen failure modes are considered, and the proposed integrated method is used to prioritize the failure modes.

Mamdani-type singleton IT2F inference model is employed in the FMEA. Additionally, the proposed model allows experts to construct their membership functions and fuzzy rules to capitalize on the experience and knowledge of the experts. The proposed group FMEA model aggregates experts' judgments by using IT2F-BWM and IT2F-WASPAS methods. The proposed model is implemented in a real-life case study in the furniture company.

The purpose of this paper is to propose novel civil aircraft cost parameters’ selection method and novel cost estimation approach for civil aircraft so as to effectively simulate or forecast civil aircraft cost under poor information and small sample.

Based on existent cost estimation indexes, this paper summarized civil aircraft research and manufacturing cost impact index system and adopted grey relational model to select most important impact factors. Consider civil aircrafts’ cost information could not be easily collected, the author must estimate their costs with limited sample and poor information. A combination model of GM (0, N) model and BP neural network algorithm is proposed. Both advantages of simulation of BP neural network algorithm and poor information generation of GM (0, N) were effectively combined. Then steps of combined model were given out. Finally, nine types of aircrafts were used to test the validity of proposed model. As comparing with the traditional multiple linear regression model and simple GM (0, N) model, results indicated that proposed model can do the work better.

Grey relational model can be applied for parameters’ selection and combined GM (0, N) model and BP neural network algorithm can estimate aircraft’s cost as well. Results show that novel combined model could get high forecasting accuracy.

Cost estimation is key problem in production management of civil aircraft. Effective cost management could promote competitiveness of aircraft manufacturing company. Proposed combined model can be applied for civil aircraft cost estimation. Similarly, it could be applied for other complex equipment cost estimation.

The paper succeeds in proposing grey relational model for cost parameters’ selection and constructing a combination model of GM (0, N) model and BP neural network algorithm. Algorithm of the proposed model was discussed and steps were given out.

The construction business is widely recognised for its inherent complexity and dynamic nature, which stems from the nature of the job involved. The industry is often regarded as one of the most challenging industries globally in terms of implementing environmental, health and safety (EHS) practices. However, in the absence of EHS, the construction industry cannot be considered sustainable. Therefore, this study aims to identify the trends, knowledge gaps and implications of EHS research to enhance construction activities and knowledge.

The study adopted a science mapping approach involving bibliometric and scientometric analysis of 407 construction EHS publications from the Scopus database with the VOSviewer software. The study is based on journal articles from the Scopus database without restriction to any time range.

The main focus of construction EHS research identified in the study includes sustainability-related studies, risk-related, environmental issues, EHS management, integrated management systems studies, health and safety related and EHS in the construction process. Some emerging areas also identified include productivity, design, culture, social sustainability and machine learning. The most influential and productive publication sources, countries/regions and EHS publications with the highest impact were also determined.

Documents published in the Scopus database were considered for analysis because of the wider coverage of the database. Journal articles written in English language represent the inclusion criteria, whereas other documents were excluded from the analysis. The study also limited the search to articles with the engineering subject area.

The research findings will enlighten stakeholders and practitioners on the focal knowledge areas in the EHS research domain, which are vital for enhancing EHS in the industry.

To the best of the authors’ knowledge, this review-based study is the first attempt to internationally conduct a science mapping on extant literature in the EHS research domain through bibliometric and scientometric assessments.

The applicability and shortcomings of a well-defined cost-estimating process to forecasting resources required for developing and fielding innovative technologies are examined. Whereas the process itself provides a suitable approach for estimating the cost of any program, investment is required for collecting historical data on analogous programs to serve as the foundation for the estimating methodologies. Particular challenges in costing innovation are summarized. An appropriate form of the cost probability distribution for research programs is offered.