Ömer Faruk Baykoç

Simulation modelling and analysis of a JIT production system

Abstract The JIT production systems have been a focus of interest to researchers. Although there are numerous simulation studies analyzing and evaluating the JIT system in a stochastic environment, experimental design studies on the multi-item, multi-line, multi-stage JIT systems are not performed in depth. This paper aims to explicitly examine the performance of a multi-item, multi-line, multi-stage JIT system and to show how this system reacts under different factor settings. This system is modeled in SLAM II, which is a FORTRAN-based simulation language. Experimental results are reported and further research direction is given

Simulation of automated guided vehicle (AGV) systems based on just-in-time (JIT) philosophy in a job-shop environment

Abstract Automated Guided Vehicle (AGV) systems have been frequently used as material handling equipment in manufacturing systems since the last two decades. The use of AGV systems has taken attention of practitioners and researchers. Although there are numerous studies concerning with AGV systems in literature, a few of them deal with the adaptation of these systems into JIT systems. Moreover, the facility layouts considered in those studies have flow-shop environment. In this paper, a simulation model of a hypothetical system which has a job shop environment and which is based on JIT philosophy was developed. In addition, a dispatching algorithm for vehicles moving through stations was presented in order to improve transportation efficiency. In given layout, multiple vehicles can move and their bi-directional flow is allowed. After the model had been established, it was mentioned how to perform simulation output analysis. The factors which may be important for the system were determined by output analysis. An experiment plan was prepared by taking into account these factors. In this plan, two levels were selected for each factor and an experimental design was conducted. The effect of each factor on each performance measure and the interaction of these factors were examined.

Assembly line balancing problem with deterioration tasks and learning effect

In this study, we introduce simultaneous effects of learning and linear deterioration into assembly line balancing problem. In many realistic settings, although the actual task time of a task is modeled as an increasing function of its starting time due to deterioration effects the produced worker(s) (or machine(s)) develops continuously by repeated the same or similar activities. The objective of problem is to minimize the station number. For this purpose, a mixed nonlinear integer programming model is developed. This paper also discusses the adaptation of the COMSOAL approach for large scale assembly line balancing problem with deterioration task and learning effect.

A possibilistic aggregate production planning model for brass casting industry

This article discusses a possibilistic aggregate production planning (APP) model for blending problem in a brass factory; the problem computing optimal amounts of raw materials for the total production of several types of brass in a planning period. The model basically has a multi-blend model formulation in which demand quantities, percentages of the ingredient in some raw materials, cost coefficients, minimum and maximum procurement amounts are all imprecise and have triangular possibility distributions. A mathematical model and a solution algorithm are proposed for solving this model. In the proposed model, the Lai and Hwangs fuzzy ranking concept is relaxed by using ‘Either-or’ constraints. An application of the brass casting APP model to a brass factory demonstrates that the proposed model successfully solves the multi-blend problem for brass casting and determines the optimal raw material purchasing policies.

Stochastic optimization for blending problem in brass casting industry

A critical process in brass casting is blending of the raw materials in a furnace so that the specified metal ratios are satisfied. The uncertainties in raw material compositions may cause violations of the specification limits and extra cost. In this study, we proposed a chance-constrained stochastic programming approach for blending problem in brass casting industry to handle the statistical variations in raw material compositions. The proposed approach is a non-linear mathematical model that is solved global optimally by using GAMS/BARON solver. An application has been performed in MKEK brass factory in Kırıkkale, Turkey and the solution of the application has been compared with alternative solution approaches based on cost and specification violation risk conditions. This comparison demonstrates that the proposed model is the most effective solution approach for managing stochastic uncertainties in blending problems and successfully can be used other industries such as alloy steel or secondary aluminum production.

An application of investment decision with random fuzzy outcomes

In this study, an investment problem associated with purchasing machine is solved by using decision trees method. The main difference of this paper from the others in the decision tree literature is using random fuzzy variables, which includes randomness and fuzziness simultaneously, for modeling demand quantities and demand state probabilities. Demand quantities and demand state probabilities are modeled as a continuous and discrete random fuzzy variables, respectively. The random fuzzy variables are transformed to fuzzy variables and crisp numbers by using the properties of the random fuzzy variable, fuzzy variable and normal distribution. After the transformation, the chance and decision nodes removals processes are performed to solve the problem.

Comparison of the Most Popular Object-Oriented Software Languages and Criterions for Introductory Programming Courses With Analytic Network Process: A Pilot Study

This study has primarily aimed at finding a tool which will facilitate the choice of programming language and making this program well‐arranged. But, choosing the proper programming language is a kind of decision making problem with multiple criterions which require the consideration of many factors which are closely interrelated. The Analytic Network Process (ANP) methodology is particularly useful for decision making in a multi‐criteria context where interaction exists between the criterions. A set of criteria for the selection of a programming language for introductory courses proposed in Parker et al. [J Inform Technol Edu USA 5: 135–142, 2006] is used in this study. These selection criterions and the criterion groups were analyzed by using the ANP, and the obtained ranking for software languages and criteria were given.

Can the uncertainty in brass casting blending problem be managed? A probability/possibility transformation approach

Problems about the uncertainty in raw material compositions are a critical issue for the blending problems. It is feared that uncertainty in raw material compositions would often cause percent values of the actual blend to go out of specification limits. In this paper, the aleatory and epistemic uncertainties have been handled simultaneously in a blending optimization problem for brass casting. The aleatory and epistemic uncertainties are modeled by using probability and possibility theories respectively. However, the probabilistic and the possibilistic uncertainties are different from the each other. Therefore to solve the mathematical model, including these uncertainties, a transformation of any type of uncertainty to the other is needed. In this study, probabilistic uncertainties are transformed to the possibilistic uncertainties by considering Rong and Lahdelmas (2008) and the Dubois, Prade, and Sandri (1993) and Dubois, Foulloy, Mauris, and Prade (2004) transformation approaches. This transformation process converts the former model to a possibilistic model. Then the possibilistic models, obtained from each transformation, are solved by using @a cuts approach. The solutions of the two possibilistic models have shown that the model, which uses Duboiss transformation, prepares blends with lower cost than the other model, which uses Rong and Lahdelmas transformation.

Simple assembly line balancing problem under the combinations of the effects of learning and deterioration

Purpose – The purpose of this paper is to describe the introduction of simple assembly line balancing problems (SALBPs) under four joint combinations of two learning effects and two deterioration effects.Design/methodology/approach – In this paper, effects of learning and deterioration are considered simultaneously. By the effects of learning and deterioration, it is meant that the task time of a task is defined by increasing function of its execution start time and position in the sequence.Findings – It was shown that polynomial solutions can be obtained for SALBP under four joint combinations of two learning effects and two deterioration effects. Furthermore, this paper also discusses the adaptations of the proposed models by using known ALB problem.Originality/value – In this paper, SALBPs were introduced under four joint combinations of two learning effects and two deterioration effects. Position dependent learning effect and time dependent learning effect were considered for learning effect when line...

AN EFFICIENTLY NOVEL MODEL FOR VEHICLE ROUTING PROBLEMS WITH STOCHASTIC DEMANDS

In this paper, the Vehicle Routing Problem with Stochastic Demands (VRPSD) is considered where customer demands are normally distributed. We propose a new model for computing the expected length of a tour. Monte Carlo simulation is used to demonstrate the accuracy of the model on randomly generated test problems. It is assumed that the service policy is non-divisible, meaning that the entire demand at each customer must be served in a single visit by a unique vehicle.