Query:  in the Semiconductor Industry

Candidate papers:

abstract: We study motives for and impacts of management discretion in inventory valuation. The semiconductor industry, with continual output price declines and rapid product obsolescence, provides an ideal setting to examine managers' inventory write down and production decisions. In this context, we develop a measure of 'excess inventory' and find that inventory write downs are strongly correlated with this measure. We also find that inventory write downs are timed strategically in periods of poor performance consistent with 'big bath' incentives. We construct a proxy for abnormal write downs, and find that it is positively associated with subsequent operating performance, and negatively associated with future write downs. Neither analysts, nor investors appear to fully appreciate the predictable implications of abnormal write downs for subsequent operating performance.
author_names: Hui Chen

Sundaresh Ramnath

Srinivasan Rangan

Steven M Rock
title: Inventory Write Downs in the Semiconductor Industry
year: 2015

abstract: I: Introductory Cases. 1. Dublin Small Animal Clinic. 2. Verona Springs Mineral Water. 3. Holton Central Chairs. 4. Chang Medical Electronics. 5. Janet O'Brien. 6. Catrike. II: Governance and Regulation. 1. Xerox. 2. Microsoft Corp: Financial Reporting Issues. 3. Beazer Homes USA. 4. Corporate Governance at IBM and Google. 5. Chrysler. 6. General Growth Properties. III: Financial Reporting, Domestic. 1. Intel Corporation: Inventory Write downs. 2. Lease Restatements in the Restaurant Industry. 3. Bethlehem Steel. 4. Revenue Recognition (A) 5. Revenue Recognition (B) 6. New Century Financial Corp. 7. Sirius XM. 8. Dell, Inc. Financial Restatements. 9. Retiree Benefits at Boeing. 10. Carton Medical Products. IV: Financial Reporting, International. 1. Impairments in the Recession of 2008 2009. 2. Depreciation in the Semiconductor Industry. 3. Thomson (A) 4. Thomson (B) 5. Mitchells Butlers. 6. Barclays' acquires Lehman. 7. SAP: Financial Reporting Methods. V: Financial Statement Analysis. 1. Harley Davidson, Inc. (A) 2. Harley Davidson, Inc. (B) 3. Arby's Acquisition of Wendy's. 4. General Motors Corp. 5. Employee Stock Options at Cisco. 6. Merrill Lynch, Inc. 7. Apple, Inc. Retrospective Adoption, Revenue Recognition Rules. VI: Valuation. 1. Knowles Electronics, Inc. 2. Anheuser Busch, Inc. 3. Inbev. 4. Sunbelt Beverage. 5. Koss. 6. Asher Associates. VII: Background Notes. 1. Note on Fair Value Reporting. 2. Note on Business Combinations. 3. Note on Discounted Cash Flows. 4. Note on Bonds. 5. Note on Retiree Benefits. 6. Note on Business Valuation. 7 Note on Ratio Analysis. VIII: Short Excel based Cases. 1. Discounted Cash Flows. 2. Revenue Recognition (A) 3. Revenue Recognition (B) 4. Impairment. 5. Bonds. 6. Leases. 7. Investment Securities. 8. Retiree Benefits. 9. Securitization. 10. Valuation.
author_names: Michael Joseph Sandretto
title: Cases in Financial Reporting
year: 2011

abstract: The International Financial Reporting Standards (IFRS) No. 2 has been the worldwide accounting principle for the reduction of inventory to market allowance since January 1, 2005. Using make to stock manufacturing strategies and inventory accounting for only approximately 14% of the total costs, integrated device manufacturers have found maintaining robust records for financial statements increasingly difficult. For example, one company in the case study conducted in this study must write down losses of 2 100% of the total inventory costs for products with inventory ages of 18months 3years. However, the average cycle time for producing flash memory is approximately 3months. In other words, when the system variation and safety stock policy are considered, the company must write down the reduction of inventory to market allowance for most of work in process inventory. However, little research has been done to addressing the practical management of operations according to inventory aging processes. This study develops a polynomial time based model to obtain significant features, including inventory ages, accounting principles, and product structures (bill of material) for the accurate prediction of inventory write downs to reduce the impact of the carrying value fluctuation of inventory. An empirical study was conducted on a Taiwanese semiconductor manufacturer. The results show that predicting 3 month inventory write downs of a complete flash memory production line comprising approximately 8500 product types can be conducted in less than 10s, with the mean absolute percentage error (MAPE) less than 3.5% Discussions regarding the sensitivity analysis and cost tornado diagrams suggest the priority of affecting factors. The results show the viability of implementing the proposed model to predict inventory write downs in the semiconductor manufacturing industry.
author_names: Jei-Zheng Wu
title: Inventory write down prediction for semiconductor manufacturing considering inventory age, accounting principle, and product structure with real settings
venue: Comput. Ind. Eng.
year: 2013

abstract: Manufacturers are making a transition to intelligent production, particularly in high tech industries. Robotic arms play a crucial role in the effectiveness of transforming processes. This research searches and analyzes patents related to robotic arms utilized by intelligent manufacturing systems. For this preliminary study, global patent trends are discussed which help evaluate the technology domain to be developed. Key words from a literature review are used to search for relevant patents, and then the patent text is analyzed using text mining software and program. The core technique applied to the patent document analysis is "Term Frequency Inverse Document Frequency" (TF IDF) Using TF IDF, the patent documents are grouped into meaningful sub technology cluster. Thus, the economic data related to the semiconductor industry is analyzed to correlate the economic impact which may be related to the transitions in technology. The data of Taiwan firms were targeted for anticipating research directions and expand intellectual property domains to invest in and pursue. For the advanced analysis, the international patent codes for global and local companies are compared. The final results help define the strength and weakness of Taiwanese robotic technology development for the semiconductor industry. Patent cluster and patent distribution analysis via a technology function matrix are the primary research approaches used for the case study. The research prepares for the development of a theoretical foundation to predict intelligent manufacturing trends.
author_names: Paul P J Chen

Amy J C Trappey

Betty H L Lin

Charles V Trappey
title: Patent Analytics of Robotics Technology for Intelligent Manufacturing in the Semiconductor Industry
venue: 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design (CSCWD)
year: 2018

abstract: Over the last years, Infineon Dresden Technologies has continuously been working on offering innovative products and enhancing the productivity of their wafer fabrication areas by increasing fab capacities as well as increasing automation in their 200 and 300 mm wafer manufacturing plants to improve productivity. One of the most important success factors is use of powerful automated material handling systems (AMHS) combined with the digitization of core processes within the whole company. Digitization supports converting a highly automated fab into a "smart fab" by horizontal and vertical integration of the internal supply chains. Within this paper, the authors provide an overview of three use cases for continuous improvement of the manufacturing process through use of automation and digitization to enhance the profitability of the semiconductor manufacturing plant.
author_names: Germar Schneider

Sophia Keil

Gerhard Luhn
title: Opportunities, challenges and use cases of digitization within the semiconductor industry
venue: 2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)
year: 2018

abstract: Three major business models are found in the semiconductor industry, namely, the integrated device manufacturer (IDM) fabless, and foundry models. IDMs design and manufacture integrated circuits (ICs) fabless companies focus only on IC design, and foundry companies are concerned only with IC manufacturing. The business model resulting when fabless and foundry companies form a strategic alliance is called the fabless foundry model. Recently, the revenue growth rate of the fabless foundry model has been considerably higher than that of IDM. This raises the question of whether the fabless foundry model will ultimately dominate the semiconductor industry or grow only to a certain extent. To investigate this, we adopted the Hodrick Prescott filter to remove the cyclic signal from original revenue data and then applied the Lotka Volterra model to analyze the competition and cooperation relationships between pairs of these business models. The results reveal that the fabless and foundry models have a mutualistic relationship, whereas IDM competes with both the fabless and foundry models. IDM and the fabless foundry model compete, but their revenues should ultimately arrive at an equilibrium point. In the long term, IDM and the fabless foundry model should coexist; the ultimate market share of IDM is predicted to be approximately 55% and that of the fabless foundry model approximately 45%
author_names: Hui-Chih Hung

Yu-Chih Chiu

Muh-Cherng Wu
title: Analysis of Competition Between IDM and Fabless Foundry Business Models in the Semiconductor Industry
venue: IEEE Transactions on Semiconductor Manufacturing
year: 2017

abstract: Abstract Automated visual inspection is an image processing technique for quality control and production line automation. This paper reviews various optical inspection approaches in the semiconductor industry and categorize the previous literatures by the inspection algorithm and inspected products. The vision based algorithms that had been adopted in the visual inspection systems include projection methods, filtering based approaches, learning based approaches, and hybrid methods. To discuss about the practical applications, the semiconductor industry covers the manufacturing and production of wafer, thin film transistor liquid crystal displays, and light emitting diodes. To improve the yield rate and reduce manufacturing costs, the inspection devices are widely installed in the design, layout, fabrication, assembly, and testing processes of production lines. To achieve a high robustness and computational efficiency of automated visual inspection, interdisciplinary knowledge between precision manufacturing and advanced image processing techniques is required in the novel system design. This paper reviews multiple defect types of various inspected products which can be referenced for further implementations and improvements.
author_names: Szu-Hao Huang

Ying-Cheng Pan
title: Automated visual inspection in the semiconductor industry: A survey
venue: Comput. Ind.
year: 2015

abstract: Atomic layer etching (ALE) is a technique for removing thin layers of material using sequential reaction steps that are self limiting. ALE has been studied in the laboratory for more than 25 years. Today, it is being driven by the semiconductor industry as an alternative to continuous etching and is viewed as an essential counterpart to atomic layer deposition. As we enter the era of atomic scale dimensions, there is need to unify the ALE field through increased effectiveness of collaboration between academia and industry, and to help enable the transition from lab to fab. With this in mind, this article provides defining criteria for ALE, along with clarification of some of the terminology and assumptions of this field. To increase understanding of the process, the mechanistic understanding is described for the silicon ALE case study, including the advantages of plasma assisted processing. A historical overview spanning more than 25 years is provided for silicon, as well as ALE studies on oxides, III V c.
author_names: Keren J Kanarik

Thorsten Lill

Eric A Hudson

Saravanapriyan Sriraman

Samantha Tan

Jeffrey Marks

Vahid Vahedi

Richard Alan Gottscho
title: Overview of atomic layer etching in the semiconductor industry
year: 2015

abstract: A wide variety of manufacturing operations can be characterized as co production with substitutable demand. That is, there are many situations in which the availability of two or more items are related, and because of randomness in either supply or demand, it can be advantageous to substitute one of these items for another. Our research was motivated by the semiconductor industry, where chips are produced in large batches. Because of the presence of randomness in the process, individual chips in a given batch can perform differently. Because some customers have stricter specifications than others, chips within the same batch can be classified and sold as different products according to their measurable performance. We model the production and inventory problem as a stochastic dynamic program in which the objective is to minimize the costs of meeting contractual obligations. After developing heuristic methods of solving the problem in practice, we validate them against a lower bound on the cost of an optimal solution to the dynamic program.
author_names: Gabriel R Bitran

Stephen M Gilbert
title: Co Production Processes with Random Yields in the Semiconductor Industry
venue: Oper. Res.
year: 1994

abstract: Currently available data suggest that most of the energy and material consumption related to the production of an integrated circuit is due to the wafer fabrication process. The complexity of wafer manufacturing, requiring hundreds of steps that vary from product to product and from facility to facility and which change every few years, has discouraged the development of material, energy, and emission inventory modules for the purpose of insertion into life cycle assessments. To address this difficulty, a flexible, process based system for estimating material requirements, energy requirements, and emissions in wafer fabrication has been developed. The method accounts for mass and energy use atthe unit operation level. Parametric unit operation modules have been developed that can be used to predict changes in inventory as the result of changes in product design, equipment selection, or process flow. A case study of the application of the modules is given for energy consumption, but a similar methodology can be used for materials, individually or aggregated.
author_names: Cynthia F Murphy

G Kenig

David T Allen

J Laurent

D E Dyer
title: Development of parametric material, energy, and emission inventories for wafer fabrication in the semiconductor industry.
venue: Environmental science technology
year: 2003