Dima Nazzal

An improved Lagrangian relaxation-based heuristic for a joint location-inventory problem

We consider a multi-echelon joint inventory-location (MJIL) problem that makes location, order assignment, and inventory decisions simultaneously. The model deals with the distribution of a single commodity from a single manufacturer to a set of retailers through a set of sites where distribution centers can be located. The retailers face deterministic demand and hold working inventory. The distribution centers order a single commodity from the manufacturer at regular intervals and distribute the product to the retailers. The distribution centers also hold working inventory representing product that has been ordered from the manufacturer but has not been yet requested by any of the retailers. Lateral supply among the distribution centers is not allowed. The problem is formulated as a nonlinear mixed-integer program, which is shown to be NP-hard. This problem has recently attracted attention, and a number of different solution approaches have been proposed to solve it. In this paper, we present a Lagrangian relaxation-based heuristic that is capable of efficiently solving large-size instances of the problem. A computational study demonstrates that our heuristic solution procedure is efficient and yields optimal or near-optimal solutions.

Survey of research in modeling conveyor-based automated material handling systems in wafer fabs

Automated material handling systems (AMHS) play a central role in modern wafer fabrication facilities (fabs). Typically, AMHS used in wafer fabs are based on discrete vehicle-based overhead systems such as overhead hoisted vehicles. Conveyor-based continuous flow transport (CFT) implementations are starting to gain support with the expectations that CFT systems will be capable of handling high-volume manufacturing transport requirements. This paper discusses literature related to models of conveyor systems in semiconductor fabs. A comprehensive overview of simulation-based models is provided. We also identify and discuss specific research problems and needs in the design and control of closed-loop conveyors. It is concluded that new analytical and simulation models of conveyor systems need to be developed to understand the behavior of such systems and bridge the gap between theoretical research and industry problems.

Scheduling setup changes at bottleneck workstations in semiconductor manufacturing

This paper presents a scheduling heuristic to aid the operators in semiconductor fabrication facilities (commonly referred to as fabs) in choosing what type of lots to process next and whether to change machine setup in order to reduce cycle time. Specifically, this study focused on developing a scheduling heuristic for ion implanters at Cirent Semiconductor (currently Agere Systems) in Orlando, Florida, where implanters are considered to be a bottleneck workstation. The re-entrant flow of production passes several times through the implanters at different stages of the wafer production, requiring changes to the current settings of the workstations and thus incurring a significant setup time. The scheduling heuristic aims at balancing workload levels for implanters processing jobs at different stages of the wafer production lifecycle. This is accomplished by first processing those jobs that contribute most to the increase in inventory levels at the bottleneck workstation. The measures used to evaluate the performance of the proposed heuristic were mean cycle time, mean work in process (WIP), and standard deviation of cycle time. The performance of the proposed heuristic was compared with the scheduling rules currently in use and other commonly used dispatching rules using a validated simulation model. Simulation results showed that the introduced heuristic performs better than all other rules in terms of mean cycle time and WIP in all cases, and better in terms of standard deviation of cycle time for most cases tested. The heuristic can be used at any bottleneck workstation that processes products at different stages of their production cycle and that requires a significant setup time.

An Analytical Model for Conveyor-Based Material Handling System With Crossovers in Semiconductor Wafer Fabs

This paper proposes a queueing-based analytical model useful in the design of closed-loop conveyor-based automated material handling system (AMHS), which has been identified as an effective material handling alternative in next-generation semiconductor wafer fabrication facilities. The model presented in this paper represents practical hardware considerations of the AMHS, such as turntables and crossovers. The objective is to accurately estimate the expected work-in-process (WIP) on the conveyor, queueing delays due to congestion at intersection points, as well as assessing the conveyor system stability. A four-phase approach is used to estimate the WIP. The proposed model is applied to the SEMATECH virtual 300 mm wafer fab. Experimental results demonstrate that in the worst case where the maximum number of crossovers is used and the traffic on the conveyor is high, the analytical model performs very well with average relative errors of 4.2%.

An analytical model for conveyor based amhs in semiconductor wafer fabs

This paper proposes an analytical model useful in the design of conveyor-based automated material handling systems (AMHS) to support semiconductor manufacturing. The objective is to correctly estimate the work-in-process on the conveyor and assess the system stability. The analysis approach is based on a queuing model, but takes into account details of the operation of the AMHS including turntables. A numerical example is provided to demonstrate and validate the queuing model over a wide range of operating scenarios. The results indicated that the analytical model estimates the expected work-in-process on the conveyor with reasonable accuracy.

Expected Response Times for Closed-Loop Multivehicle AMHS

We present an analytical approach for estimating the expected time for an automated material handling system (AMHS) to respond to move requests at loading stations in a vehicle-based, unidirectional, closed-loop AMHS. The expected response times are important for estimating the expected work-in-process (WIP) levels at the loading stations for design purposes, and for evaluating the performance of the AMHS as delayed response can impact the production cycle times. The expected response time approximation is validated by comparing the analytical model to the simulation results using a SEMATECH 300 mm hypothetical fab data set. Note to Practitioners - This paper describes an analytic method for estimating the average time for the AMHS to respond to lots ready for movement in a 300 mm wafer fab. The analysis is based on a large-scale model, requires standard solvers, and provides a very fast and reasonably accurate alternative to high-fidelity simulation. It is intended to support the early stage of fab design/redesign, allowing engineers to examine many different options before committing to the time and expense of simulation.

Throughput performance analysis for closed-loop vehicle-based material handling systems

A computationally effective analysis of the throughput performance of a closed-loop multi-vehicle automated material handling system (AMHS) used in highly automated 300 mm wafer fabrication facilities (fabs) is presented. A probabilistic model is developed, based on a detailed description of AMHS operations, and the system is analyzed as an extended Markov chain. The model represents vehicle operations on the closed-loop considering the possibility of vehicle blocking. This analysis provides essential parameters such as the vehicle blocking probabilities and the throughput capacity of the AMHS. A numerical example is analyzed and simulated using AutoMod to demonstrate and validate the stochastic model.

An analytical model of vehicle-based automated material handling systems in semiconductor fabs

This research explores analytical models useful in the design of vehicle-based automated material handling systems (AMHS) to support semiconductor manufacturing. The objective is to correctly estimate the throughput and move request delay. This analysis proposes a computationally effective analytical approach to multi-vehicle AMHS performance modeling for a simple closed loop. A probabilistic model is developed, based on a detailed description of AMHS operations, and the system is analyzed as an extended Markov chain. The model tracks the operations of one vehicle on the closed-loop considering the possibility of vehicle-blocking. This analysis provides the essential parameters such as the blocking probabilities in order to estimate the performance measures. A numerical example is analyzed and simulated using Automod to demonstrate and validate the queuing model

A greedy heuristic for locating crossovers in conveyor-based AMHS in wafer fabs

Finding the optimal layout of Automated Material Handling Systems (AMHS) is critical for the design of next generation semiconductor wafer fabs. This paper proposes a greedy heuristic to determine the configuration of a conveyor-based AMHS featuring turntables and crossovers. Using a conveyor-based analytical model, the heuristic identifies the crossover that provides the greater benefit in terms of work-in process and delivery time reduction. The virtual SEMATECH 300 mm fab is used to demonstrate the application of the heuristic. Numerical results show that adding crossovers reduced the systems delivery time by up to 22-percent in the scenarios under consideration.

Using genetic algorithms and an indifference-zone ranking and selection procedure under common random numbers for simulation optimisation

Genetic algorithms (GAs) are one of the many optimisation methodologies that have been used in conjunction with simulation modelling. The most critical step with a GA is the assignment of the selective probabilities to the alternatives. Selective probabilities are assigned based on the alternatives’ estimated performances which are obtained using simulation. An accurate estimate should be obtained to reduce the number of cases in which the search is oriented towards the wrong direction. Furthermores, it is important to obtain this estimate without many replications. This study proposes a simulation optimisation methodology that combines the GA and an indifference-zone (IZ) ranking and selection procedure under common random numbers (CRN). By using an IZ procedure, a statistical guarantee can be made about the direction in which the search should progress as well as a statistical guarantee about the results from the search. Furthermore, using CRN significantly reduces the required number of replications.