Abstracts of a variety of published technical papers relating to the use of ManSim products in semiconductor manufacturing are included below. Please use Contact Us to request the complete paper.

1. “Fab Planning: Trading in your Spreadsheet”

2. “Modeling, Scheduling, and Dispatching in the Dynamic Environment of Semiconductor Manufacturing at FASL, Japan”

3. “Workload Regulating Wafer Release in a GaAs Fab Facility”

4. “Scheduling a Semiconductor Assembly Area with Simulation Software”

5. “From Spreadsheets to Simulations: A Comparison of Analysis methods for IC Manufacturing Performance”

6. “Simulation as a Tool for Cycle Time Reduction, Equipment and Staffing Utilization, and Capacity Planning and Scheduling”

1. “Fab Planning: Trading in your Spreadsheet”
Solid State Technology, 1998
Don Baylis, Manugistics, Inc.,

Every semiconductor production manager has the responsibility of maximizing the company’s return on assets while meeting customer expectations. The classic tool for this effort – an elaborate spreadsheet – is woefully inadequate to handle the dynamics of today’s semiconductor manufacturing. Increasingly, those responsible are turning to advanced planning and scheduling software tools. Here is a guide on how to implement these tools, what to expect, and the cautions.

2. “Modeling, Scheduling, and Dispatching in the Dynamic Environment of Semiconductor Manufacturing at FASL, Japan”
SEMI/IEEE Advanced Semiconductor Manufacturing Conference, Cambridge, Massachusetts. September 1997
Brian Pickett, Advanced Micro Devices
Miguel Zuniga, Tyecin Systems

ABSTRACT: At Fujitsu AMD Semiconductor Limited (FASL), the original scheduling and dispatching process was time-consuming and inadequate to understand the effects on equipment utilization and cycle times caused by sudden changes in product mix or volume. The re-prioritizing of products due to dynamic changes in equipment status was difficult to achieve.

As with any semiconductor manufacturing facility, the flow of materials through the factory was nonlinear. This meant that linear mathematical models could not predict the behavior of the flow accurately, and that initial metrics of the factory were not sufficient to product status in the future. Furthermore, stochastic components inherent to process flows, such as equipment failures, yields, dynamic queues and reentrant flow compounded complexity.

Consequently, FASL implemented MS/S OnTime from TYECIN Systems (now ManSim, Inc.) because of its modeling, scheduling, and dispatching capabilities. To update the simulation-based scheduling with actual WIP and equipment status, the scheduler was interfaced to the MES. The coupled systems provided an almost real-time dispatching capability.

As a result of implementation, planners were able to model, schedule and dispatch all products with 95% accuracy, generate dispatch lists by operator, and perform what-if analysis of changing factory conditions. Manual operations were also reduced to a minimum.

3. “Workload Regulating Wafer Release in a GaAs Fab Facility”
Int’l Semiconductor Manufacturing Science Symposium, 1990
James W. Lawton, Al Drake, Rebecca Henderson, Lawrence M. Wein, Massachusetts Institute of Technology
Ron Whitney, Microwave Technology Division, Hewlett-Packard
Dick Zuanich, Tyecin Systems

ABSTRACT: Increased competition, both domestic and foreign, has caused a reduction in the product life of a typical instrument from ten to three years. This is placing increased pressure on Hewlett-Packard’s instrument divisions to reduce the time between new product introductions. Lengthy new circuit introduction, which is primarily a function of long fab turnaround time, is the major inhibitor in improving the introduction of new instruments. Workload regulating wafer release, a leading-edge operating policy developed a the Massachusetts Institute of Technology, is a decision rule for determining when to release a new lot of wafers in the fab. Work is fed to bottleneck stations in a systemic fashion to avoid excessive turnaround times. A workload regulating wafer release policy was developed for the Microwave Technology Division’s GaAs fab facility. Results indicate a 40-60% reduction in fab cycle time is obtainable. ManSimТ was used to model the performance increase. This paper describes the workload regulating wafer release policy that was developed for MWTD’s GaAs fab, reviews the ManSim simulation tool and how it was modified to incorporate the new wafer release policy, and closes with a brief description of the organizational factors that have led the plant to delay optimizing its wafer release policy.

4. “Scheduling a Semiconductor Assembly Area with Simulation Software”
Eighth Annual SFC/ARPA CIM-IC Workshop, August 1993
Carnegie Mellon University
Craig Weaver, Micron Semiconductor, Inc.

The semiconductor industry has experienced dramatic changes over the past decade. Scientific breakthroughs in densities and geometries have pushed the costs of manufacturing to their limits. Capital investment per die generation continues to soar unchecked. The margin of return shrinks along with die sizes. This has led the industry to focus on efforts to contain costs throughout the manufacturing process. One area that has undergone much scrutiny in the past several years is simulation scheduling. The direct recipients of these efforts have been wafer fabrication facilities. They have documented great strides in reducing cycle times and WIP which add to the bottom line. With this success in mind, it is time to include other manufacturing areas in this focus on manufacturing efficiency. Simulating the assembly/packing area is the next logical step toward a company-wide program directed at successful asset management.

The challenges facing the assembly/packaging area continue to grow with the ever-increasing part/package combinations required by semiconductor purchasers. In the arena of semiconductor manufacturing, a successful company must provide the to the customer a wide variety of products that satisfy all the needs of applications and design engineers. This depth of product line packaging inherently causes many scheduling dilemmas for assembly management. The issues include on-time delivery, work-in-process management, machine utilization, intelligent batching, bottleneck feeding, and expediting special work requests. One of the best solutions to managing these issues is simulation scheduling.

5. “From Spreadsheets to Simulations: A Comparison of Analysis methods for IC Manufacturing Performance”
International Semiconductor Manufacturing Science Symposium, 1992
Michel Baudin, MTJ
Vijay Mehrotra, O.R. PhD. Candidate, Stanford University
Barclay Tullis, Hewlett Packard, Corporation
Don Yeaman, Briner/Yeaman Engineering
Randall A. Hughes, Tyecin Systems

ABSTRACT: Today, most IC factories in the word still use spreadsheets – or spreadsheet logic embedded in mainframe software – as their only tool for capacity planning and manufacturing performance analysis. These spreadsheets are used to design multi-million dollar factories, make decisions on multi-million dollar pieces of equipment, assign special personnel, and support planning decisions over horizons of a year or more.

Spreadsheet logic can establish a minimum number of machine hours needed to sustain a particular steady-state work load. On the other hand, it is incapable of determining a sufficient number. In particular, it cannot decide whether work that appears feasible in terms of gross machine hours can actually be done through coordinated actions by operators, maintenance technicians, materials handling systems and process equipment.

We illustrate the differences between spreadsheet and simulation models through the examples of diffusion cell staffing, material flows through a process segment, and the operations of a full fab. The results show that engineering judgment applied to spreadsheet outputs is not the most prudent solution when more realistic tools are available, and that by overstating capacity, spreadsheet logic can lead to a lack ofkey equipment and space. Using similar input data, simulation models provide capacity estimates, as well as WIP and cycle time predictions, which take into account the interactions between lots, machines, and people.

Generally speaking, the spreadsheet model is inadequate to model the coordinated use of several types of resources. Until recently, the spreadsheet was still preferred in spite of its limitations because of the vast amounts of computing resources required for simulation runs. The availability of today’s cheap yet powerful computers has made this a moot point.

This paper reviews various planning approaches –from “back-of-the-envelope” calculations to discrete-event simulations, highlighting what can be expected of them as a function of the effort required. Then we examine the results of using these techniques on three examples:
1. Operator job design
2. Capacity analysis on a small process segment
3. Capacity analysis on a full-scale fab
Finally, we present recommendations for practitioners on the implementation of these techniques, and describe their place in the evolution of engineering tools.

6. “Simulation as a Tool for Cycle Time Reduction, Equipment and Staffing Utilization, and Capacity Planning and Scheduling”
U.S. Conference on GaAs MANufacturing TECHnology, 1993
Matt Morrissette, student Rochester Institute of Technology, Co-op Employment Motorola

ABSTRACT: Discrete event simulation is an effective tool for considering various manufacturing scenarios and providing information for capacity and planning decisions. Motorola’s most innovative GaAs wafer fabrication facility, Compound Semiconductor 1 (CS-1), has modeled their wafer fabrication operations and requirements with a state-of-the-art discrete event simulator call ManSimТ from Tyecin Systems (now ManSim Inc.,) ManSim is an adaptable simulation system to model the complexities and realistic details of semiconductor operations. Inputs into the model range from equipment set, staffing details, operation rules, and process steps. Outputs generated from the software include lot completion dates, throughput and cycle times, asset utilization, and capacity information. CS-1 now has the ability to capture their entire wafer fabrication process, run accurate simulations quickly, and justify capacity and planning decisions. This paper describes how CS-1 has utilized discrete event simulation to analyze fab operations to determine how to improve cycle time, asset utilization, and capacity planning in our facility.