Improving product quality while making decisions remains a challenge. The objective of this research was to develop a model that supports the precise enhancement of product quality through comprehensive analysis of possibilities, product incompatibilities, root causes, and recommended improvement actions. The model incorporated various tools and methods such as the SMARTER method, expert team selection, brainstorming, Ishikawa diagram, 5M+E rule, FAHP, and FTOPSIS methods. The study demonstrated that integrating quality management tools and decision-making methods into a unified model enables the accurate prioritization of activities for product quality management. This integrated approach represents the novelty of this research. The model was evaluated using a mechanical seal made of 410 alloy. The research findings can be valuable to enterprises seeking to enhance product quality at any stage of production, particularly for modified or new products.

The activities of the organisation concentrate mainly on meeting customers’ requirements. For this purpose, various activities are being conducted for customer satisfaction surveys. In this context, it is important to predict the quality of the product and the changes in the cost of the purchase product. The purpose of this study is to propose a method for predicting the quality level of a product and change the cost of the product considering current customers’ requirements for a combination of product feature states and pro-quality changes. The method includes the calculation of the quality level of the product using the punctationformalised method, where the level depends on a combination of values of states (parameters) attributes of the product, that is, current and modified. The method was tested as an example of a household vacuum cleaner for which 20 attributes were determined. According to the Pareto rule (20/80), the four product attributes important for customers were selected. Thereafter, for important attributes, possible combinations of the values of these attributes were determined. In addition, an algorithm for determining the possible combinations of product attribute states in the MATLAB program was developed. Additionally, the change in the current cost of the product considering the change in the quality level was estimated. The product cost changes were determined based on the actual cost of the product and the current product quality level. The method allows the determination of all combinations of values of state attributes of the product, such that it is possible to take appropriate improvement actions both in terms of quality and cost. The results from the method allow the prediction of product satisfaction for customers and they are favourable in terms of production cost. Therefore, it is possible to design the product in advance and support the producer in preparatory activities.

Modeling and simulation are key performance analysis and control techniques to optimize decision-making as well as design and operate complex production systems. They are also indicated as one of the technological pillars of modern industry and IT solutions supporting the implementation of the roadmap toward Industry 4.0 in the areas of digital transformation and automation. In the context of the required rapid transformation of today’s enterprises, it becomes extremely important to look for solutions that allow the use of the existing infrastructure, information, and energy, so as to minimize the negative impact of new technologies and the transformation process itself on the environment. The article presents an approach to modeling large and complex production systems with the use of distributed Petri net models allowing the use of the possessed IT infrastructure as consistent with the idea of sustainable development in the activities of enterprises. This eliminates two major problems that render traditional models unusable. The first is related to the difficulties in analyzing and verifying models of enormous size and infinite space of states. The second is related to the required computing power, if such analyzes are to be performed on one computing unit, which would force the producers to replace the IT infrastructure. For this purpose, modular Petri nets are introduced. Other benefits of modularization, such as smaller components that can be independently analyzed, are also presented in the paper. The proposed modular Petri net has been implemented in the proprietary GPenSIM software. The paper is complemented by a practical example of industrial modeling of production systems with automated guided vehicles (AGVs) using the Modular Model with Intelligent Petri Modules.

The article is to present the application of genetic algorithm in production scheduling in a production company. In the research work the assumptions of the methodology were described and the operation of the proposed genetic algorithm was presented in details. Genetic algorithms are useful in complex large scale combinatorial optimisation tasks and in the engineering tasks with numerous limitations in the production engineering. Moreover, they are more reliable than the existing direct search algorithms. The research is focused on the effectivity improvement and on the methodology of scheduling of a manufacturing cell work. The genetic algorithm used in the work appeared to be robust and fast in finding accurate solutions. It was shown by experiment that using this method enables obtaining schedules suitable for a model. It

The Fourth Industrial Revolution, also known as Industry 4.0, is about connecting the physical world with the virtual world in real-time. With the advent of the Fourth Industrial Revolution, manufacturing companies are introducing a number of solutions that increase productivity and personalize finished products in line with the idea of Industry 4.0. The application of, among others, the following: 3D printing, the Internet of Things, Big Data, cyber-physical systems, computing clouds, robots (collaborating and mobile), Radio-frequency identification systems, and also quality control and reverse engineering systems, is becoming popular. There are still not enough studies and analyses connected with the Polish 3D printing market, and also attempt to determine the attitude of those studies and analyses to the implementation of the Industry 4.0 conception. In connection with what is stated above, the principal objective of this paper is to determine the directions of the 3D printing industry development. In this publication, it is as well the survey respondents’ opinions relevant to opportunities and threats connected with the implementation of the Industry 4.0 conception in an enterprise are presented. The survey was conducted on a group of 100 enterprises and scientific research institutes in Poland, offering and/or applying additive technologies.