Possibilities of Evaluating the Dimensional Acceptability of Workpieces Using Computer Vision

This paper discusses the possibilities of an automated solution for determining dimensionally accurate and defective products using a computer vision system. In a real industrial environment, research was conducted on a prototype of a quality control machine, i.e. a machine that, based on product images, evaluates whether the product is accurate or defective using computer vision. Various geometric features are extracted from the obtained images of products, on the basis of which a fuzzy inference system based on Fuzzy C-means clustering features is created. The extracted geometric features represent the input variables, and the output variable has two values - true and false. The root mean square error in the evaluation of the accuracy and defectiveness of products ranges between 0.07 and 0.16. Through this research, valuable findings and conclusions were reached for the future research, since this topic is poorly examined in the most renowned databases

Investigation of Correlation between Image Features of Machined Surface and Surface Roughness

Alternative approach to surface roughness evaluation is mostly based on the analysis of digital images of machined surfaces i.e. on extracting various features from the matrix mathematically representing a digital image. This paper analyses correlation between 23 different digital image features and the surface roughness for two different materials: aluminium and stainless steel. Machined surfaces for both materials were acquired by face milling. Factorial design 6 × 5 × 2 with two replicates was conducted for each material with cutting parameters being varied on various numbers of levels. Based on the correlation coefficients the results showed that the best ranked features regardless of the machined material were the features based on statistic measures

Prilagodljivi neuro-fazi model za predviđanje tehnoloških parametara

The main goal of each technologist is the prediction of technological parameters by fulfilling the set design and technological demands. The work of the technologist is made easier by acquired knowledge and previous experience. A plan of input-output data was made by using the hybrid system of modelling ANFIS (Adaptive Neuro-Fuzzy Inference System) based on the results of seam tube production. This plan is the prerequisite for generating the system of fuzzy logic. The generated system can be used to estimate the output (speed of polishing) based on the given input (external tube diameter, oval shaping of the tube after the first phase of production, gradation of belts for grinding or polishing, condition of belts - time of usage, pressure of belts).The more precise predictions of technological time provided by the model supplement the previously defined manufacturing operations, replace the predictions based on the technologists\u27 experience and form the basis on which to plan production and control delivery times. The work of technologists is thus made easier and the production preparation technological time shorter.Procijeniti tehnološke parametre na način da se ispune postavljeni konstrukcijski i tehnološki zahtjevi cilj je i želja svakog tehnologa. Procjenu tehnologu mogu olakšati prikupljena znanja i ranije stečena iskustva. Na temelju sustavno prikupljenih podataka iz proizvodnje šavnih cijevi u radu je primjenom hibridnog sustava za modeliranje ANFIS (Adaptive Neuro-Fuzzy Inference System) oblikovan plan ulazno/izlaznih podataka. Taj je plan pretpostavka za generiranje sustava neizrazitog zaključivanja. Generirani sustav ima mogućnost procjene izlaza (brzine poliranja) na temelju danih ulaza (vanjski promjer cijevi, ovalnost cijevi nakon prve faze proizvodnje, gradacija remenja za brušenje ili poliranje, stanje remenja - vrijeme uporabe remenja, pritisak remenja). Točnije procjene tehnološkog vremena koje daje model upotpunjavaju prethodno definirane tehnološke operacije, zamjenjuje iskustvene procjene tehnologa i predstavljaju osnovu za planiranje proizvodnje i kontrolu rokova isporuke. Na ovaj se način olakšava rad tehnologa i skraćuje vrijeme tehnološke pripreme proizvodnje

Usporedba modela za procjenu tehnološkog vremena

The paper sets out to describe the results obtained by investigating the prediction of technological parameters and, indirectly, of technological time needed for seam tube polishing. The results of experimental investigations were used to define, analyse and compare two models. One is a mathematical i.e. statistical model obtained by the application of the least squares method and the least absolute deviation method. The other is a model based on the application of neural networks. To define the model based on the application of neural networks various structures of the back- propagation neural network with one hidden layer were analysed and the optimal one with the minimum RMS error was selected. The more precise predictions of technological time provided by the models supplement the previously defined manufacturing operations, replace the predictions based on the technologists’ experience and form the basis on which to plan production and control delivery times. The work of technologists is thus made easier and the production preparation technological time shorter.U radu su opisani rezultati istraživanja vezani uz procjenjivanje tehnoloških parametara i, neizravno, tehnološkog vremena poliranja šavnih cijevi. Prikupljeni su rezultati eksperimentalnih istraživanja koji su poslužili za definiranje, analizu i usporedbu dvaju modela: matematičkog, odnosno statističkog modela, za čije je postavljanje primijenjena metoda najmanjih kvadrata i metoda najmanjih apsolutnih odstupanja, i modela temeljenog na primjeni neuronskih mreža. Za definiranje modela temeljenog na primjeni neuronskih mreža analizirane su različite strukture neuronske mreže širenja unazad s jednim skrivenim slojem, te je izabrana optimalna s najmanjom razinom RMS greške. Točnije procjene tehnološkog vremena koje daju modeli upotpunjavaju prethodno definirane tehnološke operacije, zamjenjuju iskustvene procjene tehnologa i predstavljaju osnovu za planiranje proizvodnje i kontrolu rokova isporuke. Na ovaj se način olakšava rad tehnologa i skraćuje vrijeme tehnološke pripreme proizvodnje

Application of the Functional Flow Diagrams in a Design of the Level Crossing Hydraulic Barrier Drive

In a domain of a safety increasing of railway and road traffic, hydraulic barrier drives installed at level crossings have an important role. Frequent traffic accidents at level crossings, involving road vehicles and trains, are result of inappropriately equipped level crossings with signalling and safety equipment. Limited use of hydraulic barrier drives is the result of complicated adaptation in the process of implementing such systems to the existing infrastructure of some of the equipment manufacturers and railway operators. Hydraulic barrier drive PBH21, which uses a modular architecture, was developed and designed in this paper. Applying modular design principles and functional modeling methods, using functional flow diagrams, PBH21 has ability to adapt on the technologies and infrastructures of other major manufacturers of such equipment within EU countries and other countries in the world that have developed railway infrastructure. Due to the protection of certain design solutions from competition, certain details are not presented in this paper

Modelling and Prediction of Surface Roughness in CNC Turning Process using Neural Networks

The paper presents an approach to solving the problem of modelling and prediction of surface roughness in CNC turning process. In order to solve this problem an experiment was designed. Samples for experimental part of investigation were of dimensions 30 × 350 mm, and the sample material was GJS 500 - 7. Six cutting inserts were used for the designed experiment as well as variations of cutting speed, feed and depth of cut on CNC lathe DMG Moriseiki-CTX 310 Ecoline. After the conducted experiment, surface roughness of each sample was measured and a data set of 750 instances was formed. For data analysis, the Back-Propagation Neural Network (BPNN) algorithm was used. In modelling different BPNN architectures with characteristic features the results of RMS (Root Mean Square) error were controlled. Specially analysed were the RMS errors realised by different number of neurons in hidden layers. For the BPNN architecture with one hidden layer the architecture (4 – 8 - 1) was adopted with RMS error of 3,37%. In modelling the BPNN architecture with two hidden layers, a considerable amount of architectures was investigated. The adopted architecture with two hidden layers (4 - 2 - 10 - 1) generated the RMS error of 2,26%. The investigation was also directed at the size of the data set and controlling the level of RMS error

Usporedba modela za procjenu tehnološkog vremena

The paper sets out to describe the results obtained by investigating the prediction of technological parameters and, indirectly, of technological time needed for seam tube polishing. The results of experimental investigations were used to define, analyse and compare two models. One is a mathematical i.e. statistical model obtained by the application of the least squares method and the least absolute deviation method. The other is a model based on the application of neural networks. To define the model based on the application of neural networks various structures of the back- propagation neural network with one hidden layer were analysed and the optimal one with the minimum RMS error was selected. The more precise predictions of technological time provided by the models supplement the previously defined manufacturing operations, replace the predictions based on the technologists’ experience and form the basis on which to plan production and control delivery times. The work of technologists is thus made easier and the production preparation technological time shorter.U radu su opisani rezultati istraživanja vezani uz procjenjivanje tehnoloških parametara i, neizravno, tehnološkog vremena poliranja šavnih cijevi. Prikupljeni su rezultati eksperimentalnih istraživanja koji su poslužili za definiranje, analizu i usporedbu dvaju modela: matematičkog, odnosno statističkog modela, za čije je postavljanje primijenjena metoda najmanjih kvadrata i metoda najmanjih apsolutnih odstupanja, i modela temeljenog na primjeni neuronskih mreža. Za definiranje modela temeljenog na primjeni neuronskih mreža analizirane su različite strukture neuronske mreže širenja unazad s jednim skrivenim slojem, te je izabrana optimalna s najmanjom razinom RMS greške. Točnije procjene tehnološkog vremena koje daju modeli upotpunjavaju prethodno definirane tehnološke operacije, zamjenjuju iskustvene procjene tehnologa i predstavljaju osnovu za planiranje proizvodnje i kontrolu rokova isporuke. Na ovaj se način olakšava rad tehnologa i skraćuje vrijeme tehnološke pripreme proizvodnje

The role of ERP system in business process and education

U ovom radu prikazani su rezultati istraživanja pomoću ankete, provedene u 30 malih do srednje velikih poduzeća u Hrvatskoj. Razmatrane su veze između poslovnih i informacijskih aktivnosti, s naglaskom na sljedeće: stupanj znanja zaposlenika o ERP sustavima, njihovo povjerenje i odnos prema uvođenju ERP sustava, učinkovitost sustava u radnom okruženju, mogućnost reorganizacije proizvodnog procesa, ulaganje u poboljšanje sustava, integriranost sa svim odjelima u poduzeću i stupanj zadovoljstva korištenjem ERP sustava. Prema prikupljenim i analiziranim podacima može se zaključiti da je uloga korištenja ERP sustava prepoznata u mnogim poduzećima, ali još uvijek postoje određeni problemi vezani uz implementaciju, kao što su nemarnost, protivljenje i nezainteresiranost radnika. Kako bi se prevladali spomenuti nedostaci, u drugom dijelu rada je, s edukacijskog i poslovnog stajališta, opisan ERP sustav MS Dynamics NAV 2009, koji može biti izvrsna potpora za studente i zaposlenike, jer dobivanjem praktičnog znanja mogu ubrzati poslovni proces u poduzeću.In this paper, the results of the questionnaire survey conducted in 30 small to medium-size enterprises in Croatia have been presented. The authors considered the relationship between business and information activities, emphasizing also the following: the degree of knowledge about the ERP systems, employees’ response to the ERP system, the efficiency of ERP system in working environment, the possibilities of reorganization of production process, investment to improve the ERP system, integration of all departments and the degree of user satisfaction. According to the collected and analysed data, it can be concluded that the ERP systems have important role in business process, but there are some problems regarding the implementation and use of the ERP system such as inattentiveness, high resistance to change and the lack of employees’ motivation. In order to overcome the mentioned disadvantages, in the second part of the paper, MS Dynamics NAV 2009 system has been described from the educational and business process point of view as a great support for the students and employees to acquire practical knowledge and accelerate business process