Predicting the Abrasion Resistance of Tool Steels by Means of Neurofuzzy Model

This work considers use neurofuzzy set theory for estimate abrasion wear resistance of steels based on chemical composition, heat treatment (austenitising temperature, quenchant and tempering temperature), hardness after hardening and different tempering temperature and volume loss of materials according to ASTM G 65-94. Testing of volume loss for the following group of materials as fuzzy data set was taken: carbon tool steels, cold work tool steels, hot work tools steels, high-speed steels. Modelled adaptive neuro fuzzy inference system (ANFIS) is compared to statistical model of multivariable non-linear regression (MNLR). From the results it could be concluded that it is possible well estimate abrasion wear resistance for steel whose volume loss is unknown and thus eliminate unnecessary testing

Primjena metoda umjetne inteligencije pri izboru materijala

U radu je sažeto dan prikaz aktualnih metoda umjetne inteligencije: neuronskih mreža, neizrazite logike, genetičkih algoritama i ekspertnih sustava. Detaljno je opisana struktura zamišljenog inteligentnog sustava za izbor materijala u uvjetima trošenja kao i način za poboljšanje njegove glavne komponente mehanizma zaključivanja. Također su opisani i podmehanizmi glavnog mehanizma zaključivanja: mehanizam za obradu konverzacije, mehanizam za obradu asocijacija, mehanizam za obradu pravila mehanizam za obradu kriterija i izbor materijala, mehanizam za izbora postupaka modificiranja površina. U eksperimentalnom dijelu rada dan je plan izgradnje inteligentnog sustav za izbor materijala, način prikaza rezultata eksperimenta te pregled softverskih alata. Prikazani su načini mapiranja ulazno-izlaznih skupova za učenje neuronskih mreža i mehanizama zaključivanja neizrazite (fuzzy) logike. Prikazan je način kreiranja vremenskih asocijativnih matrica odgovornih za dobivanje i objašnjenje rješenja razmatranog problema. Prikazan je način optimiranja parametara neuronskih mreža genetičkim algoritmima, kao i primjena \NeuroFuzzy modela neizrazite logike. Dan je konkretni primjer načina rada mehanizma zaključivanja inteligentnog sustava za izbor materijala

Iterativna višekriterijalna metoda u optimiranju tehnološkog procesa

Estimation of production time, delivery term, production costs etc., are some of the key problems of unit production. In the previous research strong correlation was discovered between the features of the product drawing and production time, which has resulted in 8 regression equations. They were realized using stepwise multiple linear regression. Since the optimization of these regression equations did not fully define the most frequent requirements, multiobjective optimization was applied. The applied criteria included: minimum production time, maximum work costs/total costs ratio for a group of workpieces. The group was created using specific classifiers that defined similar workpieces. An iterative STEP method with seven decision variables within a group was applied, and the groups with a high index of determination were selected. Independent values that maximize the work costs/total costs ratio and minimize production times were determined. The obtained regression equations of time production parts and work costs/total costs ratio are included in the objective functions to reduce production time and increase work costs/total costs at the same time. The values of decision variables that minimize production time and maximize work costs/total costs ratio were determined. As the solution of the described problem, multicriteria iterative STEP method was applied.Procjena vremena izrade, roka isporuke, troškova izrade, itd. neki su od ključnih problema komadne proizvodnje. U prethodnom istraživanju uočena je jaka korelacijska veza između značajki nacrta proizvoda i vremena izrade koja je rezultirala s 8 regresijskih jednadžbi. One su realizirane primjenom postupne višestruke linearne regresije. Kako optimiranje tih regresijskih jednadžbi nije u potpunosti definiralo najčešće zahtjeve, primijenjena je višekriterijalna optimizacija. Kriteriji su bili: minimalno vrijeme izrade, maksimalan omjer troškova rada prema sveukupnim troškovima za grupu izradaka. Grupa je kreirana posebnim klasifikatorima koji su odredili slične izratke. Primijenjen je iterativni STEP model od sedam varijabli odluka unutar grupe, a odabrane su grupe s visokim indeksom determinacije. Određene su vrijednosti neovisnih varijabli maksimizirajući omjer troškova rada i ukupnih troškova te minimiziranjem komadnog vremena. Dobivene regresijske jednadžbe komadnog vremena izrade pozicija i omjer troškova rada prema ukupnim troškovima uključeni su u objektne funkcije kako bi se reduciralo komadno vrijeme izrade te istovremeno povećao omjer troškova rada prema ukupnim troškovima. To je odredilo vrijednosti varijabli odlučivanja koje minimiziraju komadno vrijeme i maksimiziraju omjer troškova rada prema ukupnim troškovima. Kao rješenje opisanog problema primijenjena je višekriterijalna interaktivna STEP metoda

PI/PID Controller Relay Experiment Auto-Tuning with Extended Kalman Filter and Second-Order Generalized Integrator as Parameter Estimators

This paper presents a method for the estimation of key parameters of limit cycle oscillations (amplitude and frequency) during a relay experiment used for automatic tuning of proportional-integral (PI) and proportional-integral-derivative (PID) feedback controllers. The limit cycle parameter estimator is based on the first-order extended Kalman filter (EKF) for resonance frequency estimation, to which a second-order generalized integrator (SOGI) is cascaded for the purpose of limit cycle amplitude estimation. Based on thus-obtained parameters of the limit cycle oscillations, the ultimate gain and the ultimate period of the limit cycle oscillations are estimated. These are subsequently used for the tuning of PI and PID controller according to Takahashi modifications of Ziegler-Nichols tuning rules. The proposed PI and PID controller auto-tuning method is verified by means of simulations and experimentally on the heat and air-flow experimental setup for the case of air temperature feedback control. The results have shown that the proposed auto-tuning system based on relay control experiment for the heat and air-flow process PI/PID temperature control can capture the ultimate gain and period parameters fairly quickly in simulations and in experiments. Subsequent controller tuning according to Takahashi modifications of Ziegler-Nichols rules using thus-obtained ultimate point parameters can provide favourable closed-loop load disturbance rejection, particularly in the case of PID controller

Condition Monitoring of Rotary Machinery Using Industrial IOT Framework: Step to Smart Maintenance

Modern maintenance strategies, such as predictive and prescriptive maintenance, which derived from the concept of Industry and Maintenance 4.0, involve the application of the Industrial Internet of Things (IIoT) to connect maintenance objects enabling data collection and analysis that can help make better decisions on maintenance activities. Data collection is the initial step and the foundation of any modern Predictive or Prescriptive maintenance strategy because it collects data that can then be analysed to provide useful information about the state of maintenance objects. Condition monitoring of rotary equipment is one of the most popular maintenance methods because it can distinguish machine state between multiple fault types. The topic of this paper is the presentation of an automated system for data collection, processing and interpretation of rotary equipment state that is based on IIoT framework consisting of an IIoT accelerometer, edge and fog devices, web API and database. Additionally, ISO 10816-1 guidance has been followed to develop module for evaluation of vibration severity. The collected data is also visualized in a dashboard in a near-real time and shown to maintenance engineering, which is crucial for pattern monitoring. The developed system was launched in laboratory conditions using rotating equipment failure simulator to test the logic of data collection and processing. A proposed system has shown that it is capable of automated periodic data collection and processing from remote places which is achieved using Node RED programming environment and MQTT communication protocol that enables reliable, lightweight, and secure data transmission