This paper aims to present a systematic for the analysis of the economic viability of investment projects (SAEVIP) in fixed assets. In the literature, it is possible to identify the fundamental elements to evaluate the merit of the investment project (IP). To assess the dimension 'return', indicators are analysed: net present value (NPV), NPV annualised (NPVA), index benefit/cost (IBC), return on investment annualised (ROIA), index ROIA/minimum rate of attractiveness (MRA) and return on investment (ROI). An indicator analysis for dimension 'risk' is performed by internal rate of return (IRR), Payback, index MRA/IRR, index Payback/N and Fisher point. In addition, a joint assessment of indicator of risk and return is performed. A sensitivity study is promoted on the main variables involved in economic performance of the IP (MRA, costs and revenues). To validate the SAEVIP proposal, a case study shows the wealth of information generated by the application of this systematic.Keywords: decision-making; IP; investment projects; fixed assets; economic analysis; sensitivity analysis; costs and revenues; discounted cash flow; multi-index methodology; returns and risks; verticalisation of production; planning and product development.

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PurposeThis paper examines the relationship between different manufacturing strategies and Industry 4.0's (I4.0) critical success factors (CSFs) and technology adoption.Design/methodology/approachFor that, the authors surveyed 165 practitioners from different manufacturers. Participants provided information about the levels of product customization and production volume in their companies. They also indicated the adoption level of I4.0 technologies and CSFs. Using multivariate data techniques, the authors identified four clusters of different manufacturing strategies and two readiness levels based on the establishment of I4.0 CSFs. The adoption level of I4.0 technologies was then cross compared among clusters to identify which technologies are more likely to be supported.FindingsThe findings indicate that, in low-readiness companies, the adoption level of I4.0 technologies does not significantly differ between manufacturing strategies. However, when companies present a higher I4.0 readiness, the adoption of I4.0 technologies seem to vary according to the existing manufacturing strategy.Originality/valueThis study sheds light on the influence that manufacturing strategies may have on the digital transformation of companies, highlighting which strategies are more likely to offer a context to successfully adopt I4.0 technologies. The identification of these relationships helps to define the expectation regarding the company's digital transformation, determining coherent benchmarks and allowing managers to anticipate potential issues.

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there is low risk and economic feasibility in implementation of this plant, because the probability of the Net Present Value NPV to be zero is less than 0.22%. The performed preliminary analysis showed that the decision to invest in this project is presented as a good investment option, and its implementation is recommended because it is a project with the possibility of a good financial return.

Facing the new challenges in production processes, companies should adopt lean and green practices in product development. In SMEs, the application of these practices is more complex. This work explores the maturity of lean–green methodologies in the product development process in Brazilian and Japanese SMEs. The methodology used is multicriteria, combining the analytic hierarchy process (AHP) and TOPSIS 2-tuple method, applied to four Japanese SMEs and four Brazilian SMEs in the metalworking sector. The criteria for evaluating SMEs are company flexibility, difficulties with NPD, innovation, limited resources, and personnel authority high. The TOPSIS method alternatives refer to 18 lean–green enablers. In the AHP method, the prioritisation of criteria between Japanese and Brazilian specialists presented divergences. In the Japanese context, the incidence of innovation is predominant, while in the Brazilian context, the most important is the limited resources. In the TOPSIS 2-tuple method, the results showed a higher level of maturity in lean–green methodologies in Japanese companies than in Brazilian ones. Lean practices are more evolved compared to sustainable practices in both countries. The study also addressed how open innovation adoption may contribute to innovation and NPD practices. Policymakers need to understand the heterogeneity of innovators within SMEs and how they differently innovate, developing distinct internal and external activities.

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The materials selection can affect the design component radically, with effect on the manufacturing systems efficiency, environmental impact issues, and customer satisfaction. There are different methods employed for materials selection; however, two steps are usual for most of these methods: screening and ranking. The ranking step identifies among materials candidates those that can perform the function the best as possible. Multi-criteria methods have been widely employed to materials selection, especially in the ranking step. Most of these methods take advantage of fuzzy numbers and linguistic variables to process qualitative information and information with uncertainties. One of the approaches that have been developed to solve issues related to make decisions in multi-criteria methods using linguistic information is the 2-tuple linguistic computational model. The main advantage of this approach is taking the "loss of information" away, which provides a higher precision on results. This paper aims to present a multi-criteria method for materials selection ranking step based on 2-tuple linguistic variables. The steps and several equations needed to apply the proposed method are described. Two case studies are presented and compare results with other methods to demonstrate the proposed method potential.