International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

Fourth industrial revolution also known as Industry 4.0, is a concept that significantly influences the entire operation of businesses and management. It necessitates changes in individual managerial functions, not excluding decision-making. In management theory, managerial decision making is defined in terms of content through descriptive and normative theories. The aim of the presented article is to examine the normative and descriptive understanding of decision – making in the context of adaptation of individual approaches to changes in the business environment – especially adaptation to technological progress related to the fourth industrial revolution. An overrated aspect of decision-making in this era is its rational side due to the rapid development of computer technology and the availability of rich software support. On the other hand, there is a tendency to bring to the decision-making process the involvement of all involved, collective judgment, the ability to learn from the development of the situation or openness to feedback. The understanding of the decision-making process thus moves from its traditional concept to a new understanding, which includes the above-mentioned factors. Development leads to their integration in the form of a direction that does not yet have a name but means a synergy of rational decision-making and critical thinking and reasoning in the context of descriptive theories. The overall optimal result of the decision-making process is influenced by objective criteria through a rational-normative model, environmental characteristics and subjective influences, personality, and cognitive complexity of the manager.

Grafting is the most effective way of modifying and regulating the properties of natural polysaccharides for the production of highly efficient graft copolymers, which have applications as flocculating agents for the treatment of different wastewaters. An experimental investigation connected with the modification of starch by grafting acrylamide with the application of electron beam irradiat ion is performed. In this paper the implementation of different multi-criteria optimization strategies, solving the problem with the choice between several compromise Pareto-optimal solutions are presented and compared for the process of electron beam grafting of corn starch. The compromise Pareto-optimal solutions are obtained by implementation of genetic algorithm and a set of requirements for the desired reference direction (minimum or maximum) and the constraints of the investigated quality characteristics and their variances under production conditions, which ensure the fulfilment of several goals – economic efficiency, assurance of low toxicity and high copolymer efficiency in flocculation process.

This article considers the generation of the canonical form of linear programming to determine the optimal number of techniques. The linear programming problem was solved using the created software interface as a result of solving the problem during the generation process.

The paper considers the problem of modeling agent’s choice, which allows explaining made decisions, as well as predicting possible options. The approach is based on the ideas of a subjectively rational choice. The subjectively rational choice supposes that a choice motivation is determined by external and internal factors. Internal factors represent the interests of a subject induced by his needs and ethical system he follows. External factors are induced by accepted obligations. The agent can estimate his satisfaction with the current goal-seeking state situation. The estimation might lead to changing a structure of interests, so the agent can choose it. The paper shows that when making decisions the agent uses three sets of alternatives as follows: controlling, structural and identification. This supposes the existence of three virtual sides, which choose relevant alternatives. The selection rules for such alternatives depending on subject’s awareness of the situation and the structure of his interests are formed by finding a compromise.

Production planning for the replacement of conventional manufacturing systems by new automated process chains is a com- plex activity particularly when it comes to choosing the right processes, materials and technologies. Nowadays those new process chains have to fulfil constraints such as low energy consumption and have to be resource-efficient and cost-efficient at the same time. The decision- making process can be a difficult task for authorities especially when the uncertainty of the input parameter has to be taken into account, such as prices for electricity, raw materials and lot sizes. This paper proposes a new decision-making model based on multidimensional key performance indicators (KPIs) that represent an economic and environmental objective as well as a performance objective.

This paper proposes method for ranking projects and decision-making in the selection of investment projects. This method uses Excel for decision making.

Nowadays, manufacturing systems are much larger with an increasing number of production lines and units. As a result, the decision-making of manufacturing system is a non-trivial problem and requires complex control subsystems. The use of Programmable Logic Controllers (PLCs) allows to program various and non-standard solutions. In the paper the application of Multi-Attribute Decision-Making (MADM) methods to a decision-making related to flow control in a manufacturing system with three production lines is described. For this purpose, the SAW (Simple Additive Method), WASPAS (Weighted Aggregated Sum Product ASsessment) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods are applied and simulated with using manufacturing system model in Matlab Simulink and SimEvents. In methods subjective weights defined by an expert are used. However, in order to move away from subjectivism, Shannon’s entropy is used for determining weights of criteria. The used approaches have been compared.

This article presents a computer model for optimal planning of supply and distribution of water from open irrigation canal designed to support the manager of the irrigation system in decisions on the operational management. It optimizes the supply and distribution of water among users along the canal with a criterion minimum of operational water losses. The task of optimal operational planning of water allocation was solved using the method of integer linear programming. Computer application of the integer programming model was made using MS EXCEL. The use of the model is illustrated with an example of an irrigation canal with six lateral canals.