Empirical control strategy for learning industrial robot

Današnji sistemi industrijskog robota intenzivno uključuju spoljašnje senzore kao što su kamere koje se koriste za identifikaciju objekata u radnom okruženju industrijskog robota. Uključivanjem spoljašnjih senzora-kamera problem upravljanja industrijskim robotom koji uči postaje značajno izražen. Korišćenjem empirijske upravljačke strategije, bazirane na sistemu veštačkih neuronskih mreža, industrijski robot koji uči može da ostvari adaptivno ponašanje u pogledu fleksibilnog prilagođavanja promenama u radnom okruženju. Pored prirodnih sistema koji mogu da uče na bazi iskustva, za veštačke sisteme se u dužem periodu govorilo da to nisu u stanju da ostvare. Ovaj rad ima za cilj da pokaže da je moguće ostvariti empirijsku upravljačku strategiju za industrijski robot koji uči, korišćenjem kamere i sistema veštačkih neuronskih mreža. Rezultati dobijeni korišćenjem sistema neuronskih mreža pokazali su da hvatač robota može da dođe u zahtevani položaj u odnosu na objekat hvatanja, čak i u slučaju kada je taj položaj različit od naučenih primera.Today's industrial robot systems intensively include external sensors like cameras used for identification of objects in the working environment of industrial robot. Including cameras in the system of an industrial robot, the control problem of such learning industrial robot is set. Using empirical control strategy based on application of artificial neural networks system the learning industrial robot can realize adaptive behavior in the sense of flexible adjustment to changes in the working environment. Unlike natural systems which could learn on the basis of experience, artificial systems are thought to be unable to do so for a long time. However, the concept of empirical control realizes the ability of machine learning on the basis of experience. This paper aims to show that it is possible to realize the empirical control strategy for learning industrial robot using camera and system of artificial neural networks. Results obtained by the system of neural nets have shown that the robot can move the end-effector to the desired location of the object, even in the case where the location differs slightly from the learned patterns

Empirical control strategy for learning industrial robot

Današnji sistemi industrijskog robota intenzivno uključuju spoljašnje senzore kao što su kamere koje se koriste za identifikaciju objekata u radnom okruženju industrijskog robota. Uključivanjem spoljašnjih senzora-kamera problem upravljanja industrijskim robotom koji uči postaje značajno izražen. Korišćenjem empirijske upravljačke strategije, bazirane na sistemu veštačkih neuronskih mreža, industrijski robot koji uči može da ostvari adaptivno ponašanje u pogledu fleksibilnog prilagođavanja promenama u radnom okruženju. Pored prirodnih sistema koji mogu da uče na bazi iskustva, za veštačke sisteme se u dužem periodu govorilo da to nisu u stanju da ostvare. Ovaj rad ima za cilj da pokaže da je moguće ostvariti empirijsku upravljačku strategiju za industrijski robot koji uči, korišćenjem kamere i sistema veštačkih neuronskih mreža. Rezultati dobijeni korišćenjem sistema neuronskih mreža pokazali su da hvatač robota može da dođe u zahtevani položaj u odnosu na objekat hvatanja, čak i u slučaju kada je taj položaj različit od naučenih primera.Today's industrial robot systems intensively include external sensors like cameras used for identification of objects in the working environment of industrial robot. Including cameras in the system of an industrial robot, the control problem of such learning industrial robot is set. Using empirical control strategy based on application of artificial neural networks system the learning industrial robot can realize adaptive behavior in the sense of flexible adjustment to changes in the working environment. Unlike natural systems which could learn on the basis of experience, artificial systems are thought to be unable to do so for a long time. However, the concept of empirical control realizes the ability of machine learning on the basis of experience. This paper aims to show that it is possible to realize the empirical control strategy for learning industrial robot using camera and system of artificial neural networks. Results obtained by the system of neural nets have shown that the robot can move the end-effector to the desired location of the object, even in the case where the location differs slightly from the learned patterns

QUANTITY DISCOUNTS IN SUPPLIER SELECTION PROBLEM BY USE OF FUZZY MULTI-CRITERIA PROGRAMMING

Supplier selection in supply chain is a multi-criteria problem that involves a number of quantitative and qualitative factors. This paper deals with a concrete problem of flour purchase by a company that manufactures bakery products and the purchasing price of flour depends on the quantity ordered. The criteria for supplier selection and quantities supplied by individual suppliers are: purchase costs, product quality and reliability of suppliers. The problem is solved using a model that combines revised weighting method and fuzzy multi-criteria linear programming (FMCLP). The paper highlights the efficiency of the proposed methodology in conditions when purchasing prices depend on order quantities

Machine-part family formation by using ART-1 Simulator and FLEXY

Tehnološki sistemi bazirani na konceptu grupne tehnologije imaju prednosti pre svega u domenu fleksibilnosti. U radu je, uvođenjem nove tehnike klasterovanja, analiziran odnos familije mašine-delovi unutar tehnološkog sistema i relevantnih tehnoloških procesa, s obzirom na tehnološku sličnost delova koji čine familiju. Takav tehnološki sistem se organizuje u grupe mašina, formirajući ćelije, uz obezbeđenu maksimalnu proizvodnost delova. Rad prezentira novu primenu ART-1 veštačke neuronske mreže u analizi tehnološke sličnosti i nudi modifikovan bazični pristup u cilju povećanja efikasnosti procedure klasifikovanja. Razvijeni softveri ART-1 Simulator i FLEXY su korišćeni u postupku formiranja familija, shodno reafirmisanom konceptu projektovanja grupne tehnologije.Group technology based manufacturing systems offer the advantages of flow production as well as the production flexibility of batch manufacturing. In this paper, by employing new clustering techniques, the part-machine spectrum of the manufacturing system and the relevant manufacturing process are analyzed according to design, similarity of machining and product flow. This leads to an organization of the production system into self-contained and self-regulating groups of machines called machine cells. Each machine cell undertakes a maximal production of a family of parts having similar manufacturing characteristics. This paper carried out the ART-1 neural network approach in the analysis of the manufacturing similarity, and modified the basic approach to increase the efficiency of the classification procedure. Developed program packages ART-1 Simulator and FLEXY are used to create part families and machine cells within the group technology design

The Matthew Effect in Local Welfare Policy in Croatia

The ESSPROS methodology was first used in Croatia in 2018 to collect data on social protection expenditure in local government, for the year 2017. The aim of this research is to use these data to reveal the level of social inequalities between regional government units (counties) in Croatia and to demonstrate the Matthew effect in the functioning of local welfare policies. Quantitative analysis has demonstrated a significant level of spatial and local disparities in the availability of institutional care for the elderly and children, as well as uneven social protection in terms of the provision of cash or in-kind benefits. The Matthew effect in the local social protection can be found in different forms in different social protection programmes which are provided at the local level, with the general rule that the more developed local units invest more in social services and provide greater cash benefits to their citizens. The underdevelopment of these services is particularly noticeable in the less developed, eastern part of Croatia (counties of Slavonia), while at the same time, highly developed social services are provided in the City of Zagreb. Over the last 20 years, uneven economic development and partial decentralisation have created a situation in Croatia in which one of the fundamental principles of social welfare and social policy, the principle of equality, has been seriously compromised. This has brought about the problem of double inequalities: economic ones, as a result of a lower level of development and continuous lagging behind in the development of local and regional self-government units, and social inequalities, as a result of the inability of less developed units to provide similar levels of social protection to their citizens

QUANTITY DISCOUNTS IN SUPPLIER SELECTION PROBLEM BY USE OF FUZZY MULTI-CRITERIA PROGRAMMING

Supplier selection in supply chain is a multi-criteria problem that involves a number of quantitative and qualitative factors. This paper deals with a concrete problem of flour purchase by a company that manufactures bakery products and the purchasing price of flour depends on the quantity ordered. The criteria for supplier selection and quantities supplied by individual suppliers are: purchase costs, product quality and reliability of suppliers. The problem is solved using a model that combines revised weighting method and fuzzy multi-criteria linear programming (FMCLP). The paper highlights the efficiency of the proposed methodology in conditions when purchasing prices depend on order quantities

Machine-part family formation by using ART-1 Simulator and FLEXY

Tehnološki sistemi bazirani na konceptu grupne tehnologije imaju prednosti pre svega u domenu fleksibilnosti. U radu je, uvođenjem nove tehnike klasterovanja, analiziran odnos familije mašine-delovi unutar tehnološkog sistema i relevantnih tehnoloških procesa, s obzirom na tehnološku sličnost delova koji čine familiju. Takav tehnološki sistem se organizuje u grupe mašina, formirajući ćelije, uz obezbeđenu maksimalnu proizvodnost delova. Rad prezentira novu primenu ART-1 veštačke neuronske mreže u analizi tehnološke sličnosti i nudi modifikovan bazični pristup u cilju povećanja efikasnosti procedure klasifikovanja. Razvijeni softveri ART-1 Simulator i FLEXY su korišćeni u postupku formiranja familija, shodno reafirmisanom konceptu projektovanja grupne tehnologije.Group technology based manufacturing systems offer the advantages of flow production as well as the production flexibility of batch manufacturing. In this paper, by employing new clustering techniques, the part-machine spectrum of the manufacturing system and the relevant manufacturing process are analyzed according to design, similarity of machining and product flow. This leads to an organization of the production system into self-contained and self-regulating groups of machines called machine cells. Each machine cell undertakes a maximal production of a family of parts having similar manufacturing characteristics. This paper carried out the ART-1 neural network approach in the analysis of the manufacturing similarity, and modified the basic approach to increase the efficiency of the classification procedure. Developed program packages ART-1 Simulator and FLEXY are used to create part families and machine cells within the group technology design

A fuzzy goal programming approach to solving decentralized bi-level multi-objective linear fractional programming problems

This paper presents a new approach for solving decentralized bi-level multi-objective linear fractional programming problems. The main goal was to find a simple algorithm with high confidence of decision-makers in the results. First, all the linear fractional programming models on the given set of constraints were solved separately. Next, all the linear fractional objective functions were linearized, membership functions of objective functions and decision variables controlled by decision-makers at the highest level calculated, and a fuzzy multi-objective linear programming model formed and solved as linear goal programming problem by using simplex algorithm. The efficiency of the proposed algorithm was investigated using an economic example, and the obtained results compared with those obtained using an existing method

INTEGRATION OF MULTICRITERIA ANALYSIS INTO DECISION SUPPORT CONCEPT FOR URBAN ROAD INFRASTRUCTURE MANAGEMENT

Urban road infrastructure management deals with complex decision making process. There are several reasons for a complexity such as: multi-disciplinarity, lots of participants, huge quantity of information, limited budget, conflict goals and criteria. These facts indicate that decision making processes in urban road infrastructure management belong to ill-defined problems. In order to cope with such complexity and to help managers during decision making processes this research proposes an application of multicriteria methods. Therefore, a generic concept of decision support for urban road infrastructure management based on multicriteria analysis is proposed. Three multicriteria methods: AHP, SAW and PROMETHHE, in a combination with 0-1 programming are used. The main advantage of an application of multicriteria analysis is that all stakeholders could be objectively included into decision process. Therefore, setting up of criteria weights involves opinions from all stakeholders’ groups (stakeholders are divided into three characteristic groups). Evaluation of criteria importance (weights) is based on three sets of opinions processed by Analytic Hierarchic Processing (AHP) method. Three sets of criteria are then processed by Simple Additive Weighting (SAW) method resulting in a final set of criteria weights. By using SAW method, relative importance of opinions of all three stakeholders’ groups is introduced. Collected data are then processed by PROMETHEE multicriteria methods. Proposed decision support concept is validated on the problem of improvement of one part of an urban road infrastructure system for a large urban area of town of Split. The concept is efficiently applied on several problems regarding parking garages: location selection, sub-project ranking, definition of an investment strategy