Modeling the effect of hot lots in semiconductor manufacturing systems

The presence of hot lots or high-priority jobs in semiconductor manufacturing systems is known to significantly affect the cycle time and throughput of the regular lots since the hot lots get priority at all stages of processing. In this paper, we present an efficient analytical model based on re-entrant lines and use an efficient, approximate analysis methodology for this model in order to predict the performance of a semiconductor manufacturing line in the presence of hot lots. The proposed method explicitly models scheduling policies and can be used for rapid performance analysis. Using the analytical method and also simulation, we analyze two re-entrant lines, including a full-scale model of a wafer fab, under various buffer priority scheduling policies. The numerical results show the severe effects hot lots can have on the performance characteristics of regular lots

Asymptotic loss of priority scheduling policies in closed re-entrant lines: a computational study

In this paper we present an approximate but efficient analytical method to compute the asymptotic loss of buffer priority scheduling policies in closed re-entrant lines. For simple two-station closed re-entrant lines, this enables the verification of Harrison-Wein conjectures and Jin-Ou-Kumar resuts. For multi-station re-entrant lines, this provides an efficient way of comparing different buffer priority scheduling policies. We also use the method to evaluate the effect of high priority jobs in re-entrant lines

APPROXIMATE ANALYSIS OF RE-ENTRANT LINES WITH BERNOULLI RELIABILITY MODELS

Re-entrant lines are widely used in many manufacturing systems, such as semiconductor, electronics, etc. However, the performance analysis of re-entrant lines is largely unexplored due to its complexity. In this thesis, we present iterative procedures to approximate the production rate of re-entrant lines with Bernoulli reliability of machines. The convergence of the algorithms, uniqueness of the solution, and structural properties, have been proved analytically. The accuracy of the procedures is investigated numerically. It is shown that the approaches developed can either provide a lower bound or a closed estimate of the system production rate. Finally, a case study of automotive ignition component line with re-entrant washing operations is introduced to illustrate the applicability of the method. The results of this study suggest a possible route for modeling and analysis of re-entrant systems

Analysis of Scheduling Policies for a M/G/I Queue with Rework

This thesis analyzes a multi-class M/G/1 priority queueing system in which distinct job types require one service cycle and, with non-zero probability, require a second service cycle. The main objective is to find a new heuristic scheduling policy that minimizes the long-run expected holding and preemption costs. Arrival rates, service rates, and the probability of undertaking second service are all class specific. A mean value analysis (MVA) approach was employed to derive the long- run mean time in queue for each job type under each policy, thereby providing the appropriate cost equations. Numerical experiments suggest that the preemptive resume scheduling policy yields the lowest cost most frequently

MODELING, OPTIMISATION AND ANALYSIS OF RE-ENTRANT FLOWSHOP JOB SCHEDULING WITH FUZZY PROCESSING TIMES

This paper presents a makespan minimization of -jobs -machines re-entrant flow shop scheduling problem (RFSP) under fuzzy uncertainties using Genetic Algorithm. The RFSP objective is formulated as a mathematical programme constrained by number of jobs and resources availability with traditional scheduling policies of First Come First Serve (FCFS) and the First Buffer First Serve (FBFS). Jobs processing times were specified by fuzzy numbers and modelled using triangular membership function representations. The modified centroid defuzzification technique was used at different alpha-cuts to obtain fuzzy processing times (FPT) of jobs to explore the importance of uncertainty. The traditional GA schemes and operators were used together with roulette wheel algorithm without elitism in the selection process based on job fuzzy completion times. A test problem of five jobs with specified Job Processing and Transit Times between service centres, Job Start Times and Job Due times was posed. Results obtained using the deterministic and fuzzy processing times were compared for the two different scheduling policies, FCFS and FBFS. The deterministic optimal makespan for FBFS schedule was 61.2% in excess of the FCFS policy schedule.  The results also show that schedules with fuzzy uncertainty processing times provides shorter makespans than those for deterministic processing times and those under FCFS performing better than those under FBFS policy for early jobs while on the long run the FBFS policy performs better. The results underscore the need to take account of comprehensive fuzzy uncertainties in job processing times as a trade-off between time and costs influenced by production makespan. http://dx.doi.org/10.4314/njt.v36i3.2

Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems

Improvement in the performance of production control systems is so important that many of past studies were dedicated to this problem. The applicability of fuzzy logic controllers (FLCs) in production control systems has been shown in the past literature. Furthermore, genetic algorithm (GA) has been used to optimize the FLCs performance. This is addressed as genetic fuzzy logic controller (GFLC). The GFLC methodology is used to develop two production control architectures named “genetic distributed fuzzy” (GDF), and “genetic supervisory fuzzy” (GSF) controllers. These control architectures have been applied to single-part-type production systems. In their new application, the GDF and GSF controllers are developed to control multipart- type and re-entrant production systems. In multi-part-type and re-entrant production systems the priority of production as well as the production rate for each part type is determined by production control systems. A genetic algorithm is developed to tune the membership functions (MFs) of input variables of GDF and GSF controllers. The objective function of the GSF controller is to minimize the overall production cost based on work-in-process (WIP) and backlog cost, while surplus minimization is considered in GDF controller. The GA module is programmed in MATLAB® software. The performance of each GDF or GSF controllers in controlling the production system model is evaluated using Simulink® software. The performance indices are used as chromosomes ranking criteria. The optimized GDF and GSF can be used in real implementations. GDF and GSF controllers are evaluated for two test cases namely “two-part-type production line” and “re-entrant production system”. The results have been compared with two heuristic controllers namely “heuristic distributed fuzzy” (HDF) and “heuristic supervisory fuzzy” (HSF) controllers. The results showed that GDF and GSF controllers can improve the performance of production system. In GSF control architecture, WIP level is 30% decreased rather than HSF controllers. Moreover the overall production cost is reduced in most of the test cases by 30%. GDF controllers show their abilities in reducing the backlog level but generally production cost for GDF controller is greater than GSF controller

Performance analysis of manufacturing networks : surplus-based control

In the modern market, keeping high competition in brands and varieties in type of products is the way for survival of manufacturing industries. Therefore production control methods with capabilities of quick responses to rapid changes in the demand and efficient distribution of the raw material throughout the network are of importance among leading manufacturers. Nowadays, the production control problem has been widely studied and a lot of valuable approaches including queuing theory, Petri nets, dynamic programming, linear programming, hybrid systems were proposed and some of them are implemented. Though up to this moment many methods have been developed, the factory performance remains a challenging problem for further research. Motivated by this problem we study the performance of several manufacturing networks operated by surplus-based control. In the surplus-based control, decisions are made based on the demand tracking error, which is the difference between the cumulative demand and the cumulative output of the network. The studied networks are a single machine, a manufacturing line, a multi-product manufacturing line, a re-entrant machine and a re-entrant line. The performance analysis is based on the performance factors such as demand tracking errors and inventory levels. Specifically, given the presence of unknown but bounded production speed perturbations as well as demand rate fluctuations, we investigate how close the cumulative production output of a manufacturing network follows its cumulative production demand under a surplus-based control policy. The research is subdivided into theoretical analysis, simulation-based analysis and experimental analysis parts. Theoretical analysis By means of analytical tools, the relation between the production demand tracking accuracy and the inventory levels of the networks is investigated. In order to find this relation, classical tools from control theory are used. Models of production flow processes are formulated by means of difference as well as differential equations. In order to analyze their performance, optimal control theory and Lyapunov theory approaches are exploited. Simulation based analysis By means of simulation tools, the theoretical results on performance are evaluated by time-based simulation models. Thus, all theoretical results are illustrated and confirmed by computer simulation. Also two comparative studies are conducted. The first comparative study is realized in order to test the theoretical results on more accurate models, which are event-based. The results are shown to be in agreement with the theory. The second comparative study is on time-based models, where the behavior of a line, a single re-entrant machine and a re-entrant line is tested under three commonly used surplus-based production policies. The performance of each network is evaluated and the results are presented. Experimental analysis An experimental prototype is invented, designed and developed for education and research purposes. The prototype is a hardware tool that serves as a liquid-based emulator of manufacturing network processes. In its core, the liquid-based emulator consists of several electrical pumps and liquid reservoirs. The electrical pumps emulate manufacturing machine behavior, while the liquid reservoirs serve as the intermediate product storages, also called buffers. In the platform, pumps and tanks can be interconnected in a flexible manner. In that way the prototype permits an easy and intuitive way of studying manufacturing control techniques and performance of several network topologies. A detailed system description is provided. Several network configurations and experimentations are presented and discussed

MODELING AND ANALYSIS OF SPLIT AND MERGE PRODUCTION SYSTEMS

Many production systems have split and merge operations to increase production capac- ity and variety, improve product quality, and implement product control and scheduling policies. This thesis presents analytical methods to model and analyze split and merge production systems with Bernoulli and exponential reliability machines under circulate, priority and percentage policies. The recursive procedures for performance analysis are de- rived, and the convergence of the procedures and uniqueness of the solutions, along with the structural properties, are proved analytically, and the accuracy of the estimation is justi¯ed numerically with high precision. In addition, comparisons among the e®ects of di®erent policies in system performance are carried out

Free entry in infrastructure

With a policy of free entry, individuals, firms, or community groups who wish to supply power, water, and sanitation services can do so with minimal legal restrictions. Free entry is the opposite of"exclusivity"or"legal monopoly". Free entry is allowed in most industries, but governments usually allow only one provider of power, water, and sanitation in any given area. This is supposed to prevent wasteful duplication and ensure a supply of essential services to poor and marginal areas. But monopoly water and power utilities often operate at high cost, lack funds to invest, and provide low-quality, unreliable service. Worse, poor and marginal areas are often unserved. When the monopoly model doesn't work, it is time to look at alternatives. The authors provide examples of alternative solutions in developing countries: *In Karachi, Pakistan, the Orangi Pilot Project provides sanitation in an unplanned settlement. Roughly 800,000 working class people lived in an area where sanitary conditions were medievaland a long-hoped-for sewerage system never came. Starting in 1980, a charitable group developed a low-cost approach to piped sanitation, explained the technology to the community, and catalyzed community action. Householders and neighborhoods funded the construction of household pourflush latrines and sewerage lines. * In Paraguay, 300 to 400 private individuals and aguateros supply good quality piped water to areas unserved by the public water company. Unlike the public company, the aguateros allow payment of connection fees on installment, making it easier for low-income consumers to connect. * In Yemen, small-scale electricity providers innovatively meet the rural and village demand for electricity that the public utility does not meet. These entrants seldom duplicate investments, although some government intervention to ensure interconnection could improve efficiency. Limitations on entry may sometimes be justified for environmental reasons or to promote private sector investment, but those cases are rare. Legalizing alternative providers will allow them to expand and meet new needs. Limits on their entry may be needed sometimes, but limits should be the exception, not the rule, the authors argue. Generally, free entry should be allowed in power, water, and sanitation.Health Economics&Finance,Decentralization,Water and Industry,Economic Theory&Research,Environmental Economics&Policies,Town Water Supply and Sanitation,Environmental Economics&Policies,Health Economics&Finance,Water and Industry,Economic Theory&Research

Transient analysis of manufacturing system performance

Includes bibliographical references (p. 28-34).Supported by the INDO-US Science and Technology Fellowship Program.Y. Narahari, N. Viswanadham