WIP control at end of line of semiconductor industry using CONWIP

Advancement of technology and trends in globalization has resulted in higher customer demands and expectations. Manufacturers now offer mass customization to stay competitive. In the semiconductor industry, where product mix and volume are high, production is further complicated by the different process routes and processing times for different product families. Coupled with rapid changeovers of products, it is essential to keep the work in process (WIP) low in order to reduce the inventory level on the shop floor. Constant W1P (CONWIP) is a production control strategy applicable in many manufacturing environment that use cards to control W1P level. This research was conducted in a semiconductor manufacturing company facing difficulty in reducing the variation in WIP on the shopfloor. The objectives of this research are to design and develop simulation models for single loop CONWIP, multi loop CONW1P, hybrid CONW1P, single loop CONWlP and multi loop CONWIP with buffer size optimization based on the environment in the case company. With the developed models, the maximum throughput (TH) and minimum W1P were determined. Discrete event simulation models were developed using the Witness Software for processes at the End of Line (EOL) production in the company. Experiments were conducted using these models to compare the current system with the single loop, multi loop, and hybrid CONWIP control mechanisms. ln addition, buffer optimization incorporating single loop and multi loop control were also examined. Performance parameters of TH and WIP level were compared in all experiments. The results show that CONWTP production control is more effective in reducing WlP level compared to the current system. Secondly, the single loop CONWIP showed the least number of cards in the system. However, hybrid CONWIP is more robust and provides a better control mechanism compared to the single and multi loop system. Buffer optimization control can further reduce the number of cards in the single and multi loop control. The developed simulation models are useful to determine the number of cards in the system and buffer size for each process. With these models, the production personnel can monitor and control the WJP dynamically to meet current demands and utilize the shopfloor space for more productive purposes

Variation reduction in a wafer fabrication line through inspection optimization

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 1997, and Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1997.Includes bibliographical references (p. 44).by John W. Bean.M.S

Challenges and Potentials of Digital Twins and Industry 4.0 in Product Design and Production for High Performance Products

Digital twins offer great opportunities in various domains of the product engineering process. However, current approaches to the use of digital twins only focus on different separated disciplines. In contrast to that, it is expected that the holistic use of digital twin models in product development and production will dominate future product generations, because they allow to create high-performance products competitively. This paper explores important challenges and future potentials of digital twins and Industry 4.0 for the seamless integration of product specification and production. In this regard, approaches of linking digital twins to other domains open up new possibilities in tolerance allocation and production integration. Thereby, the most efficient product specifications in technical and economic terms are achieved for the manufacturer. In addition, the connectivity of Industry 4.0 broadens the scope and enables the evaluation of alternative approaches in production planning and control. Approaches at the organizational level, product functions with specifications beyond the technological limits and production control strategies (e.g. order dispatching) ensure high performance operations. Simulations with a digital production twin with integrated digital product twin allow early estimations even before the actual ramp-up of the product. The future challenge addressed in this paper is to define a consistent framework for the holistic use of digital twins in the entire product development process, which requires the integration of product designers and production planner concepts

Stochastic optimization of product-machine qualification in a semiconductor back-end facility

abstract: In order to process a product in a semiconductor back-end facility, a machine needs to be qualified, first by having product-specific software installed and then running test wafers through it to verify that the machine is capable of performing the process correctly. In general, not all machines are qualified to process all products due to the high machine qualification cost and tool set availability. The machine qualification decision affects future capacity allocation in the facility and subsequently affects daily production schedules. To balance the tradeoff between current machine qualification costs and future potential backorder costs due to not enough machines qualified with uncertain demand, a stochastic product–machine qualification optimization model is proposed in this article. The L-shaped method and acceleration techniques are proposed to solve the stochastic model. Computational results are provided to show the necessity of the stochastic model and the performance of different solution methods.This is an Author's Accepted Manuscript of an article published as Fu, Mengying, Askin, Ronald, Fowler, John, & Zhang, Muhong (2015). Stochastic optimization of product-machine qualification in a semiconductor back-end facility. IIE TRANSACTIONS, 47(7), 739-750. DOI: 10.1080/0740817X.2014.964887. Copyright Taylor & Francis, available online at: http://www.tandfonline.com/doi/abs/10.1080/0740817X.2014.96488

Simulation and optimization techniques applied in semiconductor assembly and test operations

The importance of back-end operations in semiconductor manufacturing has been growing steadily in the face of higher customer expectations and stronger competition in the industry. In order to achieve low cycle times, high throughput, and high utilization while improving due-date performance, more effective tools are needed to support machine setup and lot dispatching decisions. In previous work, the problem of maximizing the weighted throughput of lots undergoing assembly and test (AT), while ensuring that critical lots are given priority, was investigated and a greedy randomized adaptive search procedure (GRASP) developed to find solutions. Optimization techniques have long been used for scheduling manufacturing operations on a daily basis. Solutions provide a prescription for machine setups and job processing over a finite the planning horizon. In contrast, simulation provides more detail but in a normative sense. It tells you how the system will evolve in real time for a given demand, a given set of resources and rules for using them. A simulation model can also accommodate changeovers, initial setups and multi-pass requirements easily. The first part of the research is to show how the results of an optimization model can be integrated with the decisions made within a simulation model. The problem addressed is defined in terms of four hierarchical objectives: minimize the weighted sum of key device shortages, maximize weighted throughput, minimize the number of machines used, and minimize makespan for a given set of lots in queue, and a set of resources that includes machines and tooling. The facility can be viewed as a reentrant flow shop. The basic simulation was written in AutoSched AP (ASAP) and then enhanced with the help of customization features available in the software. Several new dispatch rules were developed. Rule_First_setup is able to initialize the simulation with the setups obtained with the GRASP. Rule_All_setups enables a machine to select the setup provided by the optimization solution whenever a decision is about to be made on which setup to choose subsequent to the initial setup. Rule_Hotlot was also proposed to prioritize the processing of the hot lots that contain key devices. The objective of the second part of the research is to design and implement heuristics within the simulation model to schedule back-end operations in a semiconductor AT facility. Rule_Setupnum lets the machines determine which key device to process according to a machine setup frequency table constructed from the GRASP solution. GRASP_asap embeds a more robust selection features of GRASP in the ASAP model through customization. This allows ASAP to explore a larger portion of the feasible region at each decision point by randomizing machine setups using adaptive probability distributions that are a function of solution quality. Rule_Greedy, which is a simplification of GRASP_asap, always picks the setup for a particular machine that gives the greatest marginal improvement in the objective function among all candidates. The purpose of the third part of the research is to statistically validate the relative effectiveness of our top six dispatch rules by comparing their performance on 30 real and randomly generated data sets. Using both GRASP and our ASAP discrete event simulation model, we have (1) identified the general order of dispatch rule performance, (2) investigated the impact of having setups installed on machines at time zero on rule performance, (3) determined the conditions under which restricting the maximum number of changeover affects the rule performance, and (4) studied the factors that might simultaneously affect rule performance with the help of a common random numbers experimental design. In the analysis, the first two objectives, weighted key device shortages and weighted throughput, are used to measure outcomes.Operations Research and Industrial Engineerin

Progress in Material Handling Research: 2012

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Cognitive Radio for Emergency Networks

In the scope of the Adaptive Ad-hoc Freeband (AAF) project, an emergency network built on top of Cognitive Radio is proposed to alleviate the spectrum shortage problem which is the major limitation for emergency networks. Cognitive Radio has been proposed as a promising technology to solve todayâ?~B??~D?s spectrum scarcity problem by allowing a secondary user in the non-used parts of the spectrum that aactully are assigned to primary services. Cognitive Radio has to work in different frequency bands and various wireless channels and supports multimedia services. A heterogenous reconfigurable System-on-Chip (SoC) architecture is proposed to enable the evolution from the traditional software defined radio to Cognitive Radio