Grzegorz Kłosowski

Application of Fuzzy Logic in Assigning Workers to Production Tasks

The paper demonstrates the concept of selecting workers for production tasks with the use of fuzzy logic. Mamdani-type fuzzy inference method was used to design a controller whose task was to aid the decision-making process. Fuzzy interference system converted a number of qualitative features into quantitative variables, which enabled calculating deviations and their comparison. Moreover, a simulation model of a discrete manufacturing system with an implemented fuzzy controller was developed. conducted simulation provided detailed data regarding the investigated selection process.

Application of Fuzzy Logic Controller for Machine Load Balancing in Discrete Manufacturing System

The paper presents a concept of control of discrete manufacturing system with the use of fuzzy logic. A controller based on the concept of Mamdani was developed. The primary function realized by the controller was the balancing of machine tool loads taking into account the criteria of minimisation of machining times and costs. Two models of analogous manufacturing systems were developed, differing in the manner of assignment of production tasks to machine tools. Simulation experiments were conducted on both models and the results obtained were compared. In effect of the comparison of the results of both experiments it was demonstrated that better results were obtained in the system utilising the fuzzy inference system.

Risk-based estimation of manufacturing order costs with artificial intelligence

The following paper discusses the development of a risk-based cost estimation model for completing non-standard manufacturing orders. The model in question is a hybrid of Monte Carlo Simulation (MCS), which constitutes the main module of the applied model. Vector of order risk probability, which is the input data for the MCS module, is highly difficult to assess and is burdened to a considerable degree with subjectivity, therefore it was resolved that it should be generated with the application of artificial intelligence. Depending on the accessibility of historical data, the model incorporates fuzzy logic or artificial neural networks methods. The presented model could provide support to managers responsible for cost estimation, and moreover, after slight modification also in setting deadlines for non-standard manufacturing orders.

Integer Linear Programming in Optimization of Waste After Cutting in the Furniture Manufacturing

The study was an attempt to develop the model of a decision controller allowing for simultaneous optimisation of the stock of semi-finished product generated during cutting and cut-out waste. The proposed decision controller was designed to select a suitable cut-out programme to account for such factors as: production orders, current stock of semi-finished product, minimum stock limits, the set limit of rejects. The elaboration concerns application of integer linear programming in multicriteria optimisation in constraint.

Application of Fuzzy Logic and Genetic Algorithms in Automated Works Transport Organization

The paper deals with the problem of works transport organization and control by artificial intelligence with respect to path routing for an automated guided vehicle (AGV). The presented approach is based on non-changeable path during travel along a given loop. The ordered set of stations requesting transport service was determined by fuzzy logic, while the sequence of stations in a loop was optimized by genetic algorithms. A solution for both AGV’s and semi-autonomous transport vehicles wherein the control system informs the driver about optimal route was presented. The obtained solution was verified by a computer simulation.

Mathematical Models for Manufacturing Systems Capacity Planning and Expansion – An Overview

When planning a new manufacturing system, the optimal investment in the system capacity is a major decision to make. The problem of capacity planning is not an easy because of the unpredictable character of the market demand and multi-criteria optimization character of the task. Therefore there is still no one complex methodology of the capacity planning and management. In this paper some mathematical models for capacity planning which can be used at the stage of manufacturing system design or expansion are presented.

Human Resource Selection for Manufacturing System Using Petri Nets

Proper selection of personnel constitutes a frequent challenge for the management of many enterprises. In this paper the above problem has been defined using three objective functions which required simultaneous optimisation. To solve this problem, computer modelling based on Petri nets was proposed. The model was subjected to iterative computer simulation, during which various variants of workstation assignment were tested. This resulted in the emergence of a variant which best fulfilled the assumed optimisation criteria.

Cloud Manufacturing Concept as a Tool of Multimodal Manufacturing Systems Integration

Abstract The following article deals with a novel approach to manufacturing in the context of the increasing demand for system and process integration. This integration chiefly applies to concrete facets of manufacturing tasks which must be taken into consideration in the stage of planning and preparation for complex production processes. Those facets are primarily exemplified by order types (such as production, service and cooperative commissions etc.), production models (e.g. discrete and process modeling), product categorization based on established criteria (e.g. production technology, complexity level, used materials and extras, weight, etc.) as well as many other aspects that hold great significance in the automatization of manufacturing processes. When more advanced orders are to be realized, one of the main challenges posed by this situation is the need to accomplish multiple operations which due to their different nature, scope and scale (e.g. varied processing types: heat and plastic treating, machining etc.) have to be conducted by different contractors. In order to address those key problems and reduce the negative impact of multimodality, the author proposes a manufacturing cloud (also known as cloud manufacturing) which is a variant of a groundbreaking, yet well-established concept - cloud computing. This paper presents the chief notions of this method created specifically with integrated multimodal systems and production processes. The author also highlights key problems that should be addressed before this solution can be used in practice.

THE USE OF ARTIFICIAL INTELLIGENCE IN AUTOMATED IN-HOUSE LOGISTICS CENTRES

The paper deals with the problem of works transport organization in logistic center with the use of artificial intelligence algorithms. The presented approach is based on non-changeable path during travel along a given loop. The ordered set of containers requesting transport service was determined by fuzzy logic, while the sequence of containers in a loop was optimized by genetic algorithms. A solution for semi-autonomous transport vehicles wherein the control system informs the driver about optimal route was presented. The obtained solution was verified by a computer simulation.

Using microservices architecture as analytical system for electrical impedance tomography imaging

An image reconstruction with use of EIT method has been found useful in many areas of medical, industrial and environmental applications. Papers show that computational systems used for image reconstructions are utilizing parallel and distributed computations and multi-tier architecture, as well as monolithic architecture. The aim of our research is to define an analytical system architecture that will be able to combine a variety of image reconstruction algorithms with their representations in different programming languages. Based on examples described in different proceedings and research papers, a microservices architecture seems to be an interesting alternative to the monolithic one.