Simulation Based Study of Safety Stocks under Short-Term Demand Volatility in Integrated Device Manufacturing.

© IEOM Society InternationalA problem faced by integrated device manufacturers (IDMs) relates to fluctuating demand and can be reflected in long-term demand, middle-term demand, and short-term demand fluctuations. This paper explores safety stock under short term demand fluctuations in integrated device manufacturing. The manufacturing flow of integrated circuits is conceptualized into front end and back end operations with a die bank in between. Using a model of the back-end operations of integrated circuit manufacturing, simulation experiments were conducted based on three scenarios namely a production environment of low demand volatility and high capacity reliability (Scenario A), an environment with lower capacity reliability than scenario A (Scenario B), and an environment of high demand volatility and low capacity reliability (Scenario C). Results show trade-off relation between inventory levels and delivery performance with varied degree of severity between the different scenarios studied. Generally, higher safety stock levels are required to achieve competitive delivery performance as uncertainty in demand increases and manufacturing capability reliability decreases. Back-end cycle time are also found to have detrimental impact on delivery performance as the cycle time increases. It is suggested that success of finished goods safety stock policy relies significantly on having appropriate capacity amongst others to support fluctuations

Supply chain control: Trade-offs and system requirements

The official published version can be accessed from the link below.A paper describes the underlying forces which drive change in manufacturing enterprises and supply chains. It sets out the complexities in modern capitalism and global economics and illustrates the trade-offs that can be made. IT systems which are required to assist improvements to both customer service and enterprise manufacturing performance are explained, alluding to the special case for the semiconductor industry. Arguments are presented showing how the new tools being developed with the ESPRIT project 20544, X-CITTIC, will satisfy the control needs for a virtual enterprise. This paper describes the underlying forces which drive change in manufacturing enterprises and supply chains. It sets out the complexities in modem capitalism and global economics and illustrates the trade-offs that can be made. IT systems which are required to assist improvements to both customer service and enterprise manufacturing performance are explained alluding to the special case for the semiconductor industry. Finally it shows how the new tools being developed with the ESPRIT project 20544, XCITTIC, will satisfy the control needs for a virtual enterprise

Attaining Knowledge Workforce Agility in a Product Life Cycle Environment using Real Options

The product life cycle (PLC) phenomenon has placed significant pressures on high-tech industries which rely heavily on the knowledge workforce in transferring cutting-edge technologies into products. This thesis examines systems where market changes and production technology advances happen frequently and unpredictably during the PLC, causing difficulties in predicting an appropriate demand on the knowledge workforce and in maintaining reliable performance. Knowledge workforce agility (KWA) is identified as a desirable means for addressing the difficulties, and yet previous work on KWA is incomplete. This thesis accomplishes several critical tasks for realizing the benefits of KWA in a representative PLC environment, semiconductor manufacturing. Real options (RO) is chosen as the approach towards exploiting KWA, since RO captures the essence of KWA-options in manipulating knowledge capacity, a human asset, or a self-cultivated organizational capability for pursuing interests associated with change. Accordingly, market demand change and workforce knowledge (WK) dynamics in adoption of technology advances are formulized as underlying stochastic processes during the PLC. This thesis models KWA as capacity options in a knowledge workforce and develops a RO approach of workforce training, either initial or continuous, for generating options. To quantify the elements of KWA that impact production, the role of the knowledge workforce in production and costs in obtaining KWA are characterized mathematically. It creates necessary RO valuation methods and techniques to optimize KWA. An analytical examination of the PLC models identifies that KWA has potential to reduce negative impacts and generate opportunities in an environment of volatile demand, and to compensate unreliable performance of knowledge workforce in adoption of technology advances. The benefits of KWA are especially important when confronting highly volatile demand, a low initial adoption level, shrinking PLCs, a growing market size, intense and frequent WK dynamics, insufficient learning capability of employees, or diminishing returns from investments in learning. The thesis further assesses RO, as an agility-driven approach, by comparing it to a chase-demand heuristic and to the Bass forecasting model under demand uncertainty. The assessment demonstrates that the KWA attained from the RO approach, termed RO-based KWA, leads to a stably higher yield, to a persistently larger net present value (NPV), and to a NPV distribution that is more robust to highly volatile demand. Subsequently, a quantitative evaluation of KWA value shows that the RO-based KWA creates a considerable profit growth, either with uncertainty in demand or in the WK dynamics. In evaluation, RO modeling and the RO valuation are identified to be useful in creation of KWA value especially in highly uncertain PLC environments. This thesis illustrates the effectiveness of the numerical methods used for solving the dynamic system problem. This research demonstrates an approach for optimizing KWA in PLC environments using RO. It provides an innovative solution for knowledge workforce planning in rapidly changing and highly unexpected environments. The work of this thesis is representative of studying KWA using quantitative techniques, where there is a dearth of quantitative studies in the literature

Cycle Time Analysis For Photolithography Tools In Semiconductor Manufacturing Industry With Simulation Model : A Case Study [TR940. S618 2008 f rb].

Perkembangan industri semikonduktor dalam bidang fabrikasi biasanya melibatkan kos pelaburan yang tinggi terutamanya dalam alatan photolithography. The industry of semiconductor wafer fabrication (“fab”) has invested a huge amount of capital on the manufacturing equipments particular in photolithograph

Forecasting mix-sensitive semiconductor fabrication tool set requirements under demand uncertainty

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2001.Includes bibliographical references (leaves 74-75).by Alison L. Page.S.M.M.B.A

Controlling work in process during semiconductor assembly and test operations

In the semiconductor industry, products go through a series of steps over a three- to four-month period that begins with the fabrication of chips and ends with assembly and test (AT) and shipment. This paper introduces a mid-term planning model for scheduling AT operations aimed at minimizing the difference between customer demand and product completions each day. A secondary objective is to maximize daily throughput. Typically, semiconductor companies have 1000s of products or devices in their catalog that can be organized into unique groups of up to 100 devices each. This simplifies the planning process because it is only necessary to consider the groups as a whole rather than the individual devices when constructing schedules. In all, we developed and tested three related models. Each provides daily run rates at each processing step or logpoint for each device group for up to one month at a time. The models are distinguished by how cycle time is treated. The first takes a steady-state approach and uses Little’s Law to formulate a WIP target constraint based on the average cycle time at each processing step. The second and third include integer and fractional cycle times in the variable definitions. To find solutions, raw production data are analyzed in a preprocessing step and then converted to input files in a standard format. FlopC++ from the COIN-OR open source software project is used to write and solve the model. Testing was done using three datasets from the Taiwan AT facility of a global semiconductor firm. By comparing model output with historical data for 6 device groups and 33 logpoints, we were able to realize decreases in shortages of up to 40% per month.Mechanical Engineerin