Ensemble Sales Forecasting Study in Semiconductor Industry

Sales forecasting plays a prominent role in business planning and business strategy. The value and importance of advance information is a cornerstone of planning activity, and a well-set forecast goal can guide sale-force more efficiently. In this paper CPU sales forecasting of Intel Corporation, a multinational semiconductor industry, was considered. Past sale, future booking, exchange rates, Gross domestic product (GDP) forecasting, seasonality and other indicators were innovatively incorporated into the quantitative modeling. Benefit from the recent advances in computation power and software development, millions of models built upon multiple regressions, time series analysis, random forest and boosting tree were executed in parallel. The models with smaller validation errors were selected to form the ensemble model. To better capture the distinct characteristics, forecasting models were implemented at lead time and lines of business level. The moving windows validation process automatically selected the models which closely represent current market condition. The weekly cadence forecasting schema allowed the model to response effectively to market fluctuation. Generic variable importance analysis was also developed to increase the model interpretability. Rather than assuming fixed distribution, this non-parametric permutation variable importance analysis provided a general framework across methods to evaluate the variable importance. This variable importance framework can further extend to classification problem by modifying the mean absolute percentage error(MAPE) into misclassify error. Please find the demo code at : https://github.com/qx0731/ensemble_forecast_methodsComment: 14 pages, Industrial Conference on Data Mining 2017 (ICDM 2017

Optimizing inventory levels using financial, lifecycle and forecast variance data

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2007.Includes bibliographical references (leaves 47-48).Significant inventory write-offs have recently plagued ATI Technologies, a world leader in graphics and media processors. ATI's product-centric culture has long deterred attention from supply chain efficiency. Given that manufacturing lead time exceeds customer order lead time for its semiconductors, ATI relies heavily on their demand forecasting team to instigate supply chain activities. The PC business unit forecasting team translates market information into product-line forecast and also sets finished goods inventory levels intended to offset demand uncertainty. Today's inventory decisions are made in response to customer escalations, often ignoring financial implications. To add necessary rigor when setting these inventory levels, this thesis presents a model using wafer and unit cost, profit margin, product lifecycle stage and historical forecast error to categorize products into inventory risk levels. The resultant risk levels become a critical input to monthly demand-supply meetings with marketing, operations and senior executives - the outcome of which are wafer orders and assembly and test plans at the world's largest contract foundries and subcontractors. Finally, the 2006 acquisition of ATI by Advanced Micro Devices (AMD) offers unforeseen flexibility, scale and challenges to the outsourced semiconductor supply chain.by Irene S. Hwang.S.M.M.B.A

Modelling Small Economy Exports: The Case of Singapore

This paper sheds further light on the debate spearheaded by Riedel (1988) on the specification of a small country export function. The theoretical and empirical analyses in the paper show that while the price-taker assumption cannot be rejected, the export function for Singapore should not be construed as a standard export supply equation. As argued by Kapur (1983) instead, it is an export function with both demand and supply factors playing a role. We arrived at the final model specification by taking into consideration changes in the import content of exports over time. The paper also provides a new methodology for deriving a quarterly series of manufacturing net capital stock.price taker, demand constraint, export function, import content, restricted cointegrating space

The amplification of the bullwhip effect in the electronics industry under the influence of panic buying

Purpose: The primary purpose of this article is to show the causes and consequences of supply shortages in semiconductors for the automotive and electronics industries in 2021. The subsidiary objectives describe the behaviour of company managers that contributed to this and make proposals for strengthening the resilience of supply chains to demand impulses through their digitization and transparency of information and material flows. The stated objectives are due to the research gap in the impact of panic buying on the bullwhip effect in the supply chains.Method: The study was based on secondary and primary sources. An analysis of secondary data in the form of reports of Polish listed companies producing electronic devices for the years 2019 and 2021 was carried out in terms of inventory turnover. The year 2019 is treated as a base year, i.e., before the Covid-19 pandemic. In contrast, 2021 presents a period when electronic device manufacturers were already experiencing significant delays in semiconductor deliveries. For primary sources, one semiconductor manufacturer and three electronic device manufacturers were interviewed.Findings: The increase in demand for electronic components, extended delivery times and reduced availability has caused electronic device manufacturers to increase their purchases and inventories for fear of production stoppages, further screwing up the demand spiral and component shortages. Decisions to increase inventories were to some extent based on the practice of panic buying and demonstrated a lack of transparency in supply chains.Implications: The author proposes implementing digitalization and transparency in the supply network in place of the practice based on panic buying, which would significantly reduce production downtime for car makers and electronic device manufacturers, as well as the negative financial consequences related to production stoppages and scrapping of obsolete inventory.Keywords: bullwhip effect, panic buying, semiconductor shortage, supply chain disruptions, Covid-19Paper type: Research paperCel: Celem niniejszego artykułu było zbadanie przyczyn i skutków niedoborów w  dostawach półprzewodników dla przemysłu motoryzacyjnego i elektronicznego w  2021 roku, opisanie zachowań menedżerów przedsiębiorstw, które się do tego przyczyniły, a także przedstawienie propozycji wzmocnienia odporności sieci dostaw na impulsy popytowe poprzez ich digitalizację oraz transparentność przepływów informacyjnych i rzeczowych. Metodyka: Badanie oparto na źródłach wtórnych i pierwotnych. Przeprowadzono analizę danych wtórnych w  postaci raportów polskich spółek giełdowych produkujących urządzenia elektroniczne za lata 2019 i 2021 pod kątem rotacji zapasów. Rok 2019 traktowany jest jako bazowy, tj. jeszcze przed pandemią Covid-19. Z kolei rok 2021 prezentuje okres, w którym producenci urządzeń elektronicznych doświadczali już istotnych opóźnień w dostawach półprzewodników. W odniesieniu do źródeł pierwotnych zostały przeprowadzone wywiady z jednym producentem półprzewodników i trzema producentami urządzeń elektronicznych. Wyniki: Wzrost popytu na komponenty elektroniczne, wydłużenie czasów dostaw i ograniczenie ich dostępności spowodowało, iż producenci urządzeń elektronicznych w obawie przed postojami produkcyjnymi zwiększyli swoje zakupy i zapasy, tym bardziej nakręcając spiralę popytu i niedobory komponentów. Decyzje o powiększaniu zapasów w pewnym stopniu opierały się na praktyce dokonywania zakupów w panice i świadczyły o braku transparentności w łańcuchach dostaw. Implikacje: Autor proponuje wdrożenie digitalizacji i transparentności sieci dostaw w miejsce dokonywania zakupów w panice, co w znacznym stopniu zredukowałoby przestoje produkcyjne producentów samochodów i urządzeń elektronicznych, jak również negatywne konsekwencje finansowe związane z postojami produkcyjnymi i złomowaniem przestarzałych zapasów. Słowa kluczowe: efekt byczego bicza, zakupy dokonywane w panice, niedobory półprzewodników, zakłócenia w łańcuchu dostaw, Covid-19 Typ artykułu: Artykuł badawcz

Polycrystalline silicon material availability and market pricing outlook study for 1980 to 88: January 1983 update

Photovoltaic solar cell arrays which convert solar energy into electrical energy can become a cost effective, alternative energy source provided that an adequate supply of low priced materials and automated fabrication techniques are available. Presently, silicon is the most promising cell material for achieving the near term cost goals of the Photovoltaics Program. Electronic grade silicon is produced primarily for the semiconductor industry with the photovoltaic industry using, in most cases, the production rejects of slightly lower grade material. Therefore, the future availability of adequate supplies of low cost silicon is one of the major concerns of the Photovoltaic Program. The supply outlook for silicon with emphasis on pricing is updated and is based primarily on an industry survey conducted by a JPL consultant. This survey included interviews with polycrystalline silicon manufacturers, a large cross section of silicon users and silicon solar cell manufacturers

Polycrystalline silicon study: Low-cost silicon refining technology prospects and semiconductor-grade polycrystalline silicon availability through 1988

Photovoltaic arrays that convert solar energy into electrical energy can become a cost effective bulk energy generation alternative, provided that an adequate supply of low cost materials is available. One of the key requirements for economic photovoltaic cells is reasonably priced silicon. At present, the photovoltaic industry is dependent upon polycrystalline silicon refined by the Siemens process primarily for integrated circuits, power devices, and discrete semiconductor devices. This dependency is expected to continue until the DOE sponsored low cost silicon refining technology developments have matured to the point where they are in commercial use. The photovoltaic industry can then develop its own source of supply. Silicon material availability and market pricing projections through 1988 are updated based on data collected early in 1984. The silicon refining industry plans to meet the increasing demands of the semiconductor device and photovoltaic product industries are overviewed. In addition, the DOE sponsored technology research for producing low cost polycrystalline silicon, probabilistic cost analysis for the two most promising production processes for achieving the DOE cost goals, and the impacts of the DOE photovoltaics program silicon refining research upon the commercial polycrystalline silicon refining industry are addressed