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.

Improving the quality of industrial products quality still is a challenge. Despite using quality control, there is a constant need to support this process to achieve an effective, precise, and complex analysis of product quality. The purpose was to develop a universal model that supports improving the quality of products via the consistent and repetitive determination of the causes of product incompatibilities and actions leading to their elimination; the model can be integrated with any quality control of the product. The model verification was carried out for the incompatibility of the mechanical seal in alloy 410, in which the porosity cluster was identified by the fluorescence method (FPI). The purpose of the analysis was created by the SMART(-ER) method. Then, a team of experts was selected from which the brainstorming (BM) was realized. After the BM method, the source of incompatibility and initial causes were identified. Then, the Ishikawa diagram (according to rule 5M + E) was developed to group the initial causes. Next, during the BM method, the main causes were selected. In the last stage, the 5Why method was used to determine improvement actions, i.e., adjust clotting parameters, introduce the obligation to undergo periodic training, and set aside a separate place for storing the electrodes. Originality is the combination of selected quality management tools in a coherent model, the main aim of which is to identify the main causes of incompatibility and improvement actions. Additionally, this model is universal and has applications with analyzing any product and the causes of its incompatibility, and it can be integrated with any product quality control. Therefore, the model can be useful for improving the quality of products in any enterprise.

The main factor that conditions the success of organizations is the development of products oriented toward customer satisfaction. An additional attribute of organizations is the use of sustainable development rules. The use of these rules and the simultaneous desire to create high-quality products encourage organizations to apply different methods to, for example, eliminate waste. This study aimed to develop a method to determine the research sample size required to predict a product’s quality level, taking into account current customers’ expectations. This method was developed by modifying a procedure to determine the research sample size as part of the calculated estimator of the mean value in the general population. Based on the concept of product sustainability development, the goal of the developed method was to determine the number of potential customers (respondents) needed to provide product requirements, which were then processed and used to predict the quality level of the product. This method was applied to simultaneously test a number of hypotheses, determine the test power, and detect statistically significant differences for several relationships of the sample sizes and the test power. This was achieved using universal hypotheses and the popular alternative-punctual (MAP) method. Testing of the proposed method showed that it was able to predict the quality level of products based on current expectations of customers.

The early phases of product development effect fundamental changes in products throughout their life cycle. Therefore, the objective of the investigation was to develop a simplified model that supports the process of product design simultaneously in terms of qualitative and environmental factors. The model is dedicated to the design phase in the life cycle assessment of the product (LCA). The originality of the model consists in: (i) analysis of customers’ satisfaction from qualitative alternatives of products; (ii) assessments of the environmental impact of these alternatives; (iii) definition of the importance of qualitative and environmental attributes of products; and (iv) prediction of favourable changes in products according to qualitative–environmental levels. The model was tested for photovoltaic panels (PVs). The model is mainly dedicated to small and medium-sized enterprises (SMEs) for support in making decisions in the design phases of products in their life cycles.