Rational decision-making requires assessing the advantages and disadvantages of options, including nonmarket effects (such as environmental effects). This also applies to strategic decision-making in the industrial sector to select alternative renewable energy source (RES). Often, a variety of criteria can be used to select a renewable energy source, whereas no ideal family of criteria for renewable energy selection for industry has been defined in the literature. It was concluded that there is a need to support the actions of industrial development based on RES, which will contribute significantly to overcoming the limitations of the negative effect on the environment in terms of greenhouse gas emissions. There is a clear need for a systematic and polyvalent multicriteria approach to planning in industry. Therefore, a method for choosing the preferred renewable source of electricity for industry has been developed, which considers key criteria of RES choice: Expert opinions, the costs of obtaining the energy and maintaining energy installations, and the volume of electricity from RES. This article offers a modified multicriteria selection method based on a fuzzy analytic hierarchy process (fuzzy AHP) and the technique for preference by similarity to an ideal solution (TOPSIS), integrated with a qualitative price analysis (ACJ). This new method was tested through a case study on selecting a preferred RES in Polish industrial conditions. The research results indicate that the proposed method of choosing the preferred renewable energy source can be used in industrial enterprises that strive to meet their energy needs in accordance with the principles of social responsibility.

To conduct, in an effective way, the non-destructive testing (NDT) of products—in particular, the fluorescent penetrant inspection (FPI)—remains a challenge. Therefore, the aim of this work is to propose the method of support in the choice of a fluorescent penetrant to be used in FPI research. In the results of the usage of the proposed procedure, it is demonstrated that it is possible to reduce the negative impacts on the environment by FPI processes (through sustainability), while including other criteria, i.e., financial, security, productive (Industry 4.0), and societal (Society 5.0) criteria. The essence of the proposed method is to integrate two methods of decision support. These were the analytic hierarchy process (AHP) method and the cost–quality analysis (AKJ). Using the AHP method, the quality level of fluorescent penetrant (to the satisfaction of the customer)—which included the sustainability criteria—are calculated. These criteria include natural environment, reactivity, combustibility, level of sensitivity, and type of washing (emulsification). Then, with the help of the AKJ, the most favorable penetrant—in terms of quality and cost—is calculated and, thus, indicated. This choice must include the concept of sustainable development. Therefore, this method can be used to choose fluorescent penetrants in manufacturing and service enterprises which carry out FPI.

The publication analyses the way of managing and improving the quality of the production process of aluminum pistons for internal combustion engines. The aim of the article is to propose a method of analysis of the effectiveness of individual control methods used in the process of controlling the aluminium piston. Thanks to the location of a control point with the highest share of product non-compliance detection in the production process, it is possible to reduce quality control points by less effective points, which will contribute to lower costs or shorten the time of production processes. In view of the increasing demands on the efficiency of the checkpoints for components in internal combustion engines, the issue is important and topical.

Dynamic changes in customers’ expectations and unfavorable climate changes have generated the need to consider such aspects in the process of creating new products and the modernization of existing products. Simultaneously including customers’ expectations and environmental impact is a key element of the sustainable development of products. Enterprises attempt, within their awareness and possibilities, to apply the idea of sustainability; they do this more or less methodically. As such, an instrument to support decision-making in the area of product development is still needed because it would both be desirable for customers and have less of a negative effect on the natural environment. The purpose of this study was to develop a model that supports decision-making in the development of products while considering sustainability. The model determines the key criteria of the product, criteria states (current and future), and their positive correlations (e.g., achieving high levels of product quality and no (or a reduction in) destructive impact on the environment). To reduce the fuzzy decision-making environment, multiplicative decision methods with the fuzzy Saaty scale were implemented. These methods were the fuzzy analytic hierarchy process (FAHP) and the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The model is able to support qualitative–environment decisions in the development of any product.

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Photovoltaic electricity generation is key to achieving deep decarbonization with a high degree of electrification. It is predicted that the energy sector will reduce carbon dioxide by producing electricity mainly from photovoltaic (PV) power. Although dynamic development of the implementation of photovoltaic panels has been observed, their choice considering customer specificity is still a problem. Therefore, the purpose of this study is to propose the model of choice photovoltaic panels considering customers’ expectations. It can support the choice of a photovoltaic panel of a certain quality (satisfaction of concrete customer) in combination with the cost of its purchase. The proposed model includes acquiring and then processing customers’ expectations into technical criteria, while simultaneously considering the weighting of these criteria. It is realized in a standardized way, i.e., the zero-unitarization method (MUZ), after which normalized values of the quality of the photovoltaic panels’ criteria are obtained. In turn, the quality of these products is estimated by the weighted sum model (WSM) and then integrated with purchase cost in qualitative cost analysis (AKJ). As a result, using the scale of relative states, it is possible to categorize customer satisfaction from indicating qualitative cost and selecting the photovoltaic panel expected by customers (the most satisfactory). The effectiveness of the model was demonstrated by a sensitivity analysis, after which the key PV criteria were indicated. The proposed model is intended for any entity who selects a photovoltaic panel for customers. The computerization of calculations may contribute to its utilitarian dissemination.

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