Improving the quality of products remains a challenge. This is due to the turbulent environment and the dynamics of changing customer requirements. Hence, the key action is to predict beneficial changes in products, which will allow one to achieve customer satisfaction and reduce the waste of resources. Therefore, the purpose of this article was to develop a universal model to predict the expected direction of quality improvement. Initially, the purpose of the research was determined by using the SMART(-ER) method. Then, during the brainstorming method (BM), the product criteria and range states of these criteria were determined. Next, a survey with the Likert scale was used to obtain customers’ expectations, i.e., assessing the importance of criteria and customers’ satisfaction with ranges of product criteria states. Based on customer assessments, quality product levels were calculated using the Weighted Sum Model (WSM). Then, the initial customer satisfaction from the product quality level was identified according to the relative state’s scale. Based on this, the direction of product quality improvement was anticipated using the Naïve Bayesian Classifier (NBC). A test of the model was carried out for photovoltaic panels (PV) of a key EU producer. However, the proposed model is universal, because it can be used by any entity to predict the direction of improvement of any kind of product. The originality of this model allows the prediction of the destination of product improvement according to customers’ assessments for weights of criteria and satisfaction from ranges of quality-criterion states.

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.

The current situation in the energy market contributes not only to the sales growth of photovoltaic panels (PV) but also to the intense search for possibilities for its improvement. The purpose of this research was to develop a model to determine, where possible, the most beneficial modifications to improve products. The model used combination techniques, i.e., the SMARTER method, brainstorming (BM), the 7 ± 2 rule, questionnaire, ant colony optimization (ACO), and importance-performance analysis (IPA). In addition, an algorithm supporting ACO was proposed in the MATLAB program. The test was carried out on PV and showed that it is possible to determine the way of product (PV) improvement by determining a sequence of modifications for product criteria states while simultaneously considering customers’ expectations. It was shown that each state of the short-circuit electricity and peak power was satisfactory for customers. It was necessary to modify the maximum current and idle voltage. In addition, the selected modification states of the weight and dimensions will be more satisfactory compared to the current states. The proposed model is based on searching for the best changes in product criteria to achieve the highest possible customer satisfaction (i.e., product quality level). Originality is the ability to define a product improvement method (PV) depending on customer expectations but also taking into account the requirements of the company.

The foundry industry consumes significant amounts of natural resources, metals, and energy, and it generates large amounts of solid waste and gases, which have a significant impact on the environment. Therefore, taking sustainability-based improvement measures in foundry companies is necessary and an important part of sustainable development for humanity. The aim of this study was to develop a universal indicator model for quality control improvement focused on the foundry industry. The model allows a multi-criteria analysis of various quality control methods and the determination of their gradation in the context of ensuring an objectively high level of product quality. A test of the model carried out in foundry companies confirmed its suitability. An optimisation of the relationship between product quality and quality control efficiency was carried out, which fulfilled the criteria of efficiency, reliability, low emissivity, low energy intensity, low cost, short lead time, and automation. Thanks to the indicated features, the model clearly fits into the concept of sustainable development and Industry 4.0. The result of the realised research, i.e., the ranking of the gradation of detection methods, allowed optimisation of quality control within the analysed production process. Future research directions will address the integration of digital solutions within the model.