Jesus A. Jimenez

Levels of Capacity and Material Handling System Modeling for Factory Integration Decision Making in Semiconductor Wafer Fabs

As the costs of building a new wafer fab increase, a detailed simulation model representing the production operations, the tools, the automated material handling systems (AMHS), and the tool-AMHS interactions is needed for accurately planning the capacity of these facilities. The problem is that it currently takes too long to build, experiment, and analyze a sufficiently detailed model of a fab. The key for building accurate and computationally efficient fab models is to decide on the right amount of model details, specifically those details representing the equipment capacity and the AMHS. This paper identifies a method for classifying a fab model by the level of capacity detail, the level of AMHS detail, or the level of capacity/AMHS detail. Within the capacity/ AMHS modeling level, our method further differentiates between detailed integrated capacity/AMHS models and abstract coupled capacity/AMHS models. The proposed classification method serves as the basis of a framework that helps users select the system components to be modeled within a desired level of detail. This research also provides a review of past-published literature summarizing the work done at each of the proposed fab modeling levels. A case study comparing the performance between an integrated capacity/AMHS model and a coupled capacity/AMHS model is presented. The study demonstrates that the coupled model generates cycle time estimates that are not statistically different than those generated by the integrated model. This paper also shows that the coupled model can improve CPU time by approximately 98% in relation to the integrated model.

Designing a Sustainable and Distributed Generation System for Semiconductor Wafer Fabs

Driven by wind and solar photovoltaics technology, the power industry is shifting towards a distributed generation (DG) paradigm. A key challenge in deploying a renewable DG system is the power volatility. This study proposes a visionary energy concept and further presents a mathematical model that could help the large industry consumers adopt this new energy technology. The study seeks to design a grid-connected DG system that is capable of providing the necessary electricity for wafer fabs. Simulation-based optimization algorithm was applied to determine the equipment type and capacity aiming to minimize the DG lifecycle cost. The proposed method was demonstrated on fab facilitates located in three different regions in the US.

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%.

Review on planning and automation technologies for distributed generation systems

As renewable energy penetrates the utility market, the electricity industry is undergoing a paradigm shift that will change the industry to generate electricity using distributed generation systems. Consequently, there are new opportunities for enhancing the utility companys power quality and network reliability, as well as increasing their level of automation. This paper surveys the most recent advances in planning, optimization, and automation for distributed generation systems. Our emphasis is on explaining how renewable sources of energy, such as wind power and solar photovoltaic, are integrated into the distributed generation systems. Our review covers both deterministic and probabilistic methods of planning. Automation in power quality monitoring, network control, and fault detection are discussed. There is an increased interest on using smart grids for distributed energy production, distribution, and consumption. Therefore, our paper identifies critical directions for future research in this area.

Optimising the automated plasma cutting process by design of experiments

Automated plasma cutting is an effective process for building complex, two-dimensional metallic parts in a short period of time. Because the plasma cutting machine has several factors or input variables to control (e.g., current, cutting speed, torch height, etc.) and the process requires compliance with a variety of part quality characteristics or response variables (e.g., flatness, clean cut, bevel angle, etc.), it is difficult to find a machine setting that improves the overall quality of the manufactured parts. This research was conducted to discover the relevant factors that affect the parts surface quality characteristics and the optimum machine settings by implementing a design of experiments and following a response surface methodology approach. Desirability functions were used to optimise the automated plasma cutting process. Final results identified an optimal machine configuration that facilitates the fabrication of parts with close-to-perfect quality for all the 18 quality responses considered.

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.

Modeling and simulation of patient admission services in a multi-specialty outpatient clinic

Tactical planning of resources in healthcare clinics concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to serve the strategically agreed number of patients, and to use resources efficiently. In this paper, we describe a simulation model for an outpatient healthcare clinic facing multiple issues related to patient admission and resource workflow. The main problems identified at the clinic are: 1) phones are not answered promptly and 2) patients experience long wait time to check in and check out. The simulation model focuses on the front desk operations. We investigate different resource allocation policies and report on computational results based on a real clinic, historical data, and both patient and management performance measures.

Simulating conveyor-based AMHS layout configurations in small wafer lot manufacturing environments

Automated material handling systems (AMHS) using conveyors have been recently proposed as a technology option for next generation wafer fabrication facilities. This technology seems to provide an increasing capacity for moving and storing wafers in a continuous flow transport environment. The goal of this research is to design and test conveyor-based AMHS configurations, which include turntables and storage areas near the processing equipment. Simulation models were developed in AutoMod to determine the best conveyor layout, with emphasis in comparing centralized versus distributed storage systems. The AMHS factors under study comprise the number, location, and capacity of the storage areas. Simulation results show that the distributed storage approach provides improved performance; however, these systems require more capital investment than that needed for the centralized storage approach.

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.

Exploring a solar photovoltaic-based energy solution for green manufacturing industry

A large amount of electricity is required to support the operation of large manufacturing facilities. Integrating renewable energy into the manufacturing industry reduces the carbon footprint and ensures the long-term sustainability. A key challenge in deploying renewable technology is the power volatility. We propose a solar photovoltaic-based co-generation system to accommodate the electricity needs of semiconductor wafer fabs. The problem is formulated as a stochastic programming model with the goal to minimize the system cost subject to the loss-of-load probability constraint. We compare the renewable energy yield and the system cost at five different wafer fabs in the U.S. Given appropriate tax incentives or equipment subsidies, the study shows that the solar-based energy solution is economically competitive in regions where the overcast days are less than 35% of the year.