Rule based heuristic approach for minimizing total flow time in permutation flow shop scheduling

Programiranje radova u proizvodnji je od bitne važnosti u planiranju i funkcioniranju proizvodnog sustava. Unaprijeđeni sustav programiranja značajno utječe na smanjenje troškova i minimalni broj radnih postupaka. U ovom se radu razmatra problem programiranja n/m/F/ΣCi primjenom Decision Tree (DT) algoritma. Budući da je ovaj problem poznat kao veoma NP-hard, u radu se za njegovo rješenje predlaže metodologija temeljena na heuristici. Prednosti DT-a su u tome što je pravilo otpreme u obliku If-then else pravila koja radnici u radionici lako razumiju. Predloženi je pristup testiran na repernim problemima dostupnim u literaturi i uspoređen. Predloženi rad je dodatak tradicionalnim metodama.Production scheduling plays a vital role in the planning and operation of a manufacturing system. Better scheduling system has a significant impact on cost reduction and minimum work-in-process inventory. This work considers the problem of scheduling n/m/F/ΣCi using Decision Tree (DT) algorithm. Since this problem is known to be strongly NP-hard, this work proposes heuristic based methodology to solve it. The advantages of DT’s are that the dispatching rule is in the form of If-then else rules which are easily understandable by the shop floor people. The proposed approach is tested on benchmark problems available in the literature and compared. The proposed work is a complement to the traditional methods

Optimization of cylindrical grinding process parameters using meta-heuristic algorithms

389-395Owing to the complexity of grinding process, it has been very difficult to predict the optimal machining conditions which have been resulted in smooth surface finish, accurate geometric measurements and higher production rate. In this work, empirical models for surface roughness, roundness error and metal removal rate have been developed based on regression analysis. These models have been associated the grinding process parameters (work speed, feed rate and depth of cut) with machining performances (metal removal rate, roundness error and surface roughness). Using these models, the optimization has been carried out based on simulated annealing (SA) and genetic algorithm (GA) which have been the two popular meta-heuristic optimization techniques. Finally, the results of the proposed techniques l have compared and experimentally validated

Optimization of cylindrical grinding process parameters using meta-heuristic algorithms

Owing to the complexity of grinding process, it has been very difficult to predict the optimal machining conditionswhich have been resulted in smooth surface finish, accurate geometric measurements and higher production rate. In thiswork, empirical models for surface roughness, roundness error and metal removal rate have been developed based onregression analysis. These models have been associated the grinding process parameters (work speed, feed rate and depth ofcut) with machining performances (metal removal rate, roundness error and surface roughness). Using these models, theoptimization has been carried out based on simulated annealing (SA) and genetic algorithm (GA) which have been the twopopular meta-heuristic optimization techniques. Finally, the results of the proposed techniques l have compared andexperimentally validated