Intelligent System Supporting Technological Process Planning for Machining

Abstract

The aim of the study was to develop a system supporting technological process planning, the functioning of which would resemble the way human experts act in their fields of expertise, one capable of gathering necessary knowledge, analysing data, and drawing conclusions to solve problems. This could be done by utilising artificial intelligence (AI) methods available within such systems. The study proved the usefulness of AI methods, and their significant effectiveness in supporting technological process planning. Technological-process planning based on an expert system is divided into the following stages: the selection of the semi-finished products; the establishing of the technological process structure, and the selection of the workpiece instrumentation, machine tools, tools, and tooling and machining parameters for each technological operation. The system-embedded knowledge takes the form of neural networks, decision trees and facts. The system is presented using the example of a real enterprise. The intelligent expert system is dedicated to process engineers who have not yet gathered sufficient experience in technological-process planning, or who have just begun their work in a given production enterprise, and are not very familiar with its machinery and other means of production.

Bim-Based Prototype of a Mathematical Model of Construction Planning

“…Most of the optimization methods present in the literature are used to solve local optimization problems (Rojek et al, 2021;Cekus et al, 2022), because the analyzed algorithms do not cover all construction processes, i.e., they do not fully cover the selection of machinery, designing temporary roads and storage sites, temporary engineering networks, etc. Due to the fact that BIM modeling usually focuses only on building design, we consider a mathematical algorithm that is used only for the comprehensive optimization of planning and organization of a construction site.…”

Environmental analysis of a product manufactured with the use of an additive technology – AI-based vs. traditional approaches

“…In order to minimize the negative environmental impact of, inter alia, new technologies, in 2015 the World Commission on Environment and Development [5] defined 17 sustainable development goals and 169 targets. Aimed to help implement the sustainable development policy, they are accompanied by the concept of sustainable manufacturing, defined as the creation of manufactured products that use processes which minimize negative environmental impacts, conserve energy and natural resources, are safe for employees, communities, and consumers, and also economically sound [6][7][8]. Sustainable manufacturing encompasses not only manufacturing, but also preparatory and post-manufacturing processes, such as designing, procurement of raw materials, distribution, use and reuse of the product.…”

Bulletin of the Polish Academy of Sciences: Technical Sciences

“…The emerging research areas regarding modern technologies in the sustainable development of Industry 4.0 include industrial policy (circular economy, economic factors, development of industrial production, description of added value), Industry 4.0 and sustainable production, industrial Internet of Things and sustainable development, intelligent production (optimization, flexibility, maintenance), sustainable development and life cycle management, Cyber-Physical Systems (CPS), Smart Factory and small and medium-sized enterprises (SMEs), large data sets, among others (logistics 4.0, collaboration, additive manufacturing) [15,[48][49][50][51][52].…”