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The 2019 International Conference on Modeling and Analysis of Semiconductor Manufacturing (MASM 2019) was part of the 2019 Winter Simulation Conference (WSC) that was held December 8–11 in National Harbor, MD, USA. The MASM conferences provide a forum for the exchange of ideas and industrial innovations between researchers and practitioners from around the world involved in modeling and analysis of complex high-tech manufacturing systems. While the papers from MASM conferences are of high quality and are often cited in journal papers, they are limited in size. As a premier journal for topics covered in the MASM conferences, IEEE Transactions on Semiconductor Manufacturing, agreed to consider extended article submissions based on the 21 papers accepted and presented at the MASM 2019 conference for a Special Section of an upcoming issue of the journal. were sessions on Scheduling and Dispatching, Fab Scheduling, Maintenance and Engineering, Capacity and Production Planning, Qualification and Wafer-to-Order Allocation, Semiconductor Manufacturing Models, and Semiconductor Modeling Representations. Dr. Sabine Herlitschka, Chief Executive Officer and Chief Technology Officer of Infineon Technologies Austria AG, gave an excellent keynote talk titled “A European View on Future Semiconductor Industry Needs for MASM.” An archive of the MASM 2019 papers can be found at https://informs-sim.org/wsc19papers/by_area.html. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

We are pleased to announce that the June 2022 issue of the IEEE Transactions on Dielectrics and Electrical Insulation (TDEI) will be a special issue on electrets and related phenomena. This issue is open to all authors. Presenters of papers at the IEEE 18th International Symposium on Electrets (ISE18) to be held during September 24–28, 2021 in Shanghai (China) are especially encouraged to submit their work to this special issue. For more information on ISE18 please go to https://ise18.tongji.edu.cn/. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

The "IEEE Transactions on Semiconductor Manufacturing" is a journal that publishes the latest advancements in the manufacturing of microelectronic and photonic components. It aims to enhance knowledge and improve manufacturing practices in the semiconductor industry. The journal covers various topics such as process integration, manufacturing equipment performance, yield analysis, metrology, and supply chain management. Papers submitted to the journal should focus on practical engineering techniques for solving manufacturing-related problems. The journal follows a peer-review process and encourages authors from low-income countries to submit their work. The standard length for regular papers is eight pages, and shorter contributions can be submitted as letters. The journal provides guidelines for manuscript preparation, including the use of the IEEE template style. It also accepts graphical abstracts and electronic supplements. Authors are responsible for preparing a publication-quality manuscript and may use English language editing services if needed. Plagiarism is strictly prohibited, and manuscripts found to have plagiarized content may be penalized. Authors are required to have an Open Researcher and Contributor ID (ORCID) and can submit their manuscripts online. The journal offers both traditional and open access publication options, with associated fees. Native language author names are supported, and page charges may apply for publication. The IEEE holds the copyright to the published material. [Extracted from the article]

The 2022 ASMC, our 33rd, returned to Saratoga Springs, NY as an in-person conference after 2 years as a virtual conference. While we are all grateful for the digital world’s enhancements that allowed this conference to be held remotely, attendees were happy to return to an in-person event where networking is much easier. [ABSTRACT FROM AUTHOR]

High quality scholarship requires technical excellence but also connects the work to the primary references in the field. In this way the reader advances their knowledge and gains perspective. The Transactions on Semiconductor Manufacturing supports these goals by recognizing the best paper chosen by the Associate Editors and reviewers. The winning paper was selected from 51 papers published by TSM in 2016. The winner is “Risk-Controlled Product Mix Planning in Semiconductor Manufacturing Using Simulation Optimization” by Dr. Kuo-Hao Chang published in the November 2016 issue of IEEE Transactions on Semiconductor Manufacturing (10.1109/TSM.2016.2602388). Dr. Chang is a professor of Industrial Engineering and Engineering Manufacturing at National Tsing Hua University in Hsinchu, Taiwan. The paper applies a method developed in another domain to find the optimal product mix in a semiconductor manufacturing line. On behalf of the associate editors, I congratulate Dr. Chang on being selected. [ABSTRACT FROM AUTHOR]

Each year the Transactions on Semiconductor Manufacturing recognizes the best paper published during the previous calendar year. This year 12 papers were nominated by our reviewers and members of our Editorial Board and Steering Committee. The paper entitled “Maximizing Output During Ramp by Integrating Capacity and Velocity” by Adar A. Kalir and Kosta Rozen of Intel Corporation (vol. 31, no. 3, August 2018) was recognized as the Best Paper of 2018. The authors examine the very important problem of managing starts into a wafer fab during the ramp-up of new capacity, and find that maintaining starts slightly below constraint capacity to reduce cycle times can actually increase total output over the ramp-up duration. [ABSTRACT FROM AUTHOR]

As guest editor for the Special Section on the 2019 International Conference on Compound Semiconductor Manufacturing Technology (CS-MANTECH), I am gratified to be able to present IEEE Transactions on Semiconductor Manufacturing readers with a selection of papers based on work presented at the 2019 edition of the conference. The CS-MANTECH conference is a unique technical forum for presenting advancements in compound semiconductor devices. A special strength of CS-MANTECH is its strong emphasis on manufacturing technologies associated with compound semiconductor manufacturing. While devices based on compound semiconductors have long been used in high-performance RF, microwave, and millimeter-wave systems, in recent years compound-semiconductors have been increasingly finding their way into power systems (through advancements in SiC, GaN, Ga2O3, and other wide band gap device technologies). In addition, while compound semiconductors have long been essential for optoelectronic applications such as detectors, LEDs, and lasers, the widespread commercialization of these technologies has led to rapid advances in volume manufacturing of these devices. Additionally, trends towards tighter integration with silicon-based technologies to provide enhanced system-level performance and functionality have been accelerating, providing further opportunities for advancements in compound semiconductor manufacturing. [ABSTRACT FROM AUTHOR]

The increasing availability of data, advances in computational and storage capacities of IT systems, and algorithmic advances in Artificial Intelligence (AI), especially Machine Learning (ML) combine to enable significant improvements in the efficiency, operations and throughput of manufacturing systems at the production level. The semiconductor industry is one of the most data-intensive industries and has seen increased use of AI-based technologies over the last few years. In order to develop effective AI-based technologies in the semiconductor manufacturing industry several issues have to be taken into account, including scalability, heterogeneity of data, and the need for interpretability. [ABSTRACT FROM AUTHOR]

Each year the Transactions on Semiconductor Manufacturing recognizes the best paper published during the previous calendar year. This year 9 papers were nominated by our reviewers and members of our Editorial Board and Steering Committee, out of a total of 78 papers published in our pages in 2017. From among these, the members of the Editorial Board and Steering Committee selected the paper entitled “A Novel Dynamic Process Control Scheme to Improve Cycle Time in Fabs” by Dr. Michael Hassoun of the Department of Industrial Engineering and Management of Ariel University in Israel. This paper continues an ongoing line of research examining the impact of process control policies on the tradeoff between cycle time and yield in wafer fabrication. The primary finding is that modest relaxation of process control parameters to reduce time spent adjusting production equipment when it is in high demand can often reduce cycle time with minimal negative impact. A number of fruitful extensions for future work are also discussed, holding out the possibility of improved integration of scheduling and process control techniques. On behalf of the TSM community, I have the pleasure of congratulating Dr. Hassoun on this recognition, and of wishing him continued success in future. [ABSTRACT FROM AUTHOR]

As a guest Editor for the special section on the 2017, 2018, and 2019 International Conference on Microelectronic Test Structures (ICMTS), I am gratified to be able to present our IEEE Transactions on Semiconductor Manufacturing readers with a selection of papers based on work presented at the 2017, 2018, and 2019 conferences. [ABSTRACT FROM AUTHOR]

The IEEE Transactions on Semiconductor Manufacturing congratulates Haoyu Yang, Shuhe Li, Wen Chen, Piyush Pathak, Frank Gennari, Ya-Chieh Lai, and Bei Yu whose paper DeePattern: Layout Pattern Generation With Transforming Convolutional Auto-Encoder (Vol. 35, No.1, February 2022) was selected as the Best Paper for 2022 by a team of Associate Editors. This paper proposes generative machine learning models to synthesize VLSI layouts through a pattern generation framework that reduces the challenging creation problem into two simpler subproblems with the aid of an efficient squish pattern representation. The problem is treated by designing an innovative transforming convolutional auto-encoder in TCAE architecture, aiming to generate efficient and representative pattern shapes. The paper introduces a GAN-guided TCAE ML analysis that targets massive DRC-clean and content-specific pattern generation following certain design rules, without losing pattern library diversity. Through experiments on 7nm EUV designs, the authors demonstrate that each latent vector node in TCAE has a real physical meanings in layout domain and transformations on latent vectors can produce additional topologies of interest. Results show that the generated pattern library exhibits larger pattern number and pattern diversity compared to the traditional state-of-the-art industry layout generator. [ABSTRACT FROM AUTHOR]

Semiconductor vertical furnaces must achieve even faster and more precise temperature control due to the demand for ever-reducing the minimum feature size or critical dimension in semiconductor chips. Also, the insulation performance of vertical furnaces has improved to reduce power consumption; as a side effect, temperature reduction operation takes longer without active cooling. Therefore, in addition to heaters, vertical furnaces equipped with coolers have emerged to achieve higher productivity, more precise temperature control, and lower power consumption. However, the inability to generate positive and negative control inputs for one of the heaters or coolers poses a challenge for an intuitive controller parameter design. The aim of this paper is to address these issues by proposing an intuitive method for designing a controller in the frequency domain which virtually integrates heaters and coolers. We implemented the controller in a full-scale actual semiconductor vertical furnace and first confirmed that the linearity is high. Furthermore, we experimentally verified that the controller achieves both high-speed, high-precision temperature control and low power consumption. [ABSTRACT FROM AUTHOR]

This is a panel paper that discusses the use of Artificial Intelligence (AI) technologies to address production and supply chain level problems in semiconductor manufacturing. We have gathered a group of expert semiconductor researchers and practitioners from around the world who have developed AI solutions for various semiconductor problems. This paper aims to provide their answers to an initial set of questions and provide an overview of the AI developments and empirical studies to make suggestions for future directions in this arena. [ABSTRACT FROM AUTHOR]

High quality scholarship requires technical excellence but also connects the work to the primary references in the field. In this way, the reader advances their knowledge and gains perspective. The TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING supports these goals by recognizing the best paper chosen by the Associate Editors and reviewers. The winning paper was selected from 140 papers published by TSM in 2015. The winner is “An Algorithm of Multi-Subpopulation Parameters With Hybrid Estimation of Distribution for Semiconductor Scheduling With Constrained Waiting Time” by Hung-Kai Wang, Chen-Fu Chien, and Mitsuo Gen published in the August 2015 issue of the IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING (10.1109/TSM.2015.2439054). I congratulate the authors on their selection. [ABSTRACT FROM AUTHOR]

High quality scholarship requires technical excellence and also connects the work to the primary references in the field. In this way, the reader advances their knowledge and gains perspective. The IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING (TSM) supports these goals by recognizing the best paper chosen by the Associate Editors and reviewers. The winning paper was selected from 59 papers published by the TSM in 2014. The winner is “Feasibility Evaluation of Virtual Metrology for the Example of a Trench Etch Process” by Georg Roeder, Sirko Winzer, Martin Schellenberger, Stefan Jank, and Lothar Pfitzner published in the August 2014 issue of the IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING (10.1109/TSM.2014.2321192). Congratulations to the authors on being selected. [ABSTRACT FROM AUTHOR]

The IEEE Transactions on Semiconductor Manufacturing congratulates Yonghwi Kwon and Youngsoo Shin whose paper Optical Proximity Correction Using Bidirectional Recurrent Neural Network With Attention Mechanism was selected as the Best paper for 2021. The paper was selected from all the papers that appeared in 2021 by a team of Associate Editors. This paper applied recurrent neural networks to optical proximity correction for lithographic processing for integrated circuits. The challenge in determining a correction value comes from correlation: correction of one segment affects the correction value of other segments due to the optical proximity effect. This paper broke new ground by showing that Recurrent Neural Networks, which has been mainly applied to time series data, can be effectively applied to spatial data. Clearly, Machine Learning is rapidly moving from R&D into full flow manufacturing where the interplay between each aspect of a single process step has exponential increased in complexity requiring new approaches. Three additional papers were recognized with an Honorable Mention: [ABSTRACT FROM AUTHOR]

Welcome to the January 2022 issue of the IEEE Transactions on Visualization and Computer Graphics (TVCG). This is traditionally the time of the year when we feature the IEEE VIS special issue and this year is no different. But there is one significant difference — IEEE VIS is now fully unified. There is no more IEEE VAST, IEEE InfoVis and IEEE SciVis; there is just IEEE VIS, tiled into six overarching areas: Applications (24 papers), Analytics & Decisions (19), Theoretical & Empirical (24), Representations & Interaction (19), Data Transformations (14) and Systems & Rendering (11). The conference was scheduled to take place in New Orleans (LA) but was moved to a virtual event due to the global coronavirus pandemic. This virtual conference took place from October 24-29, 2021. Contained in this special issue are the top 110 papers selected by the unified program committee from a total of 441 submissions. In addition, this issue also contains the Best Paper of the 2021 IEEE Large Scale Data Analysis and Visualization (LDAV) Symposium and the Best Paper of the 2021 IEEE Symposium on Visualization for Cyber Security (VizSec). [ABSTRACT FROM AUTHOR]

This special section of IEEE Transactions on Semiconductor Manufacturing presents extended versions of papers originally presented as part of the IEEE 33rd International Conference on Microelectronic Test Structures (ICMTS) which was hosted at the University of Edinburgh, Scotland. Originally planned to take place at the University’s South Hall Complex in April 2020, the impact of the global pandemic led to the difficult decision to move to a fully virtual conference held between 4th – 18th May 2020. The guest editors for this special section, who were honoured to act as the General Chair and Technical Chair of the conference, would like to thank all of those involved in making the virtual conference a success, not least the digital events team from the IEEE who made it possible. [ABSTRACT FROM AUTHOR]

I am pleased to announce the Best Paper for the TRANSACTIONS published in 2013. [ABSTRACT FROM AUTHOR]

This paper proposes a linear regression model for scalar-valued responses and two-way functional (bivariate) predictors. Our motivation stems from the quality evaluation of products based on optical emission spectroscopy data from virtual metrology of semiconductor manufacturing. We focus on multivariate cases where the smoothness and shapes of the data vary significantly across variables. We propose a two-step solution to this problem, consisting of decomposition and prediction. First, we decompose the two-way functional data into pairs of component functions using functional singular value decomposition. Next, we build functional linear models for the decomposed functional variables and obtain the final predictor by averaging the models. Results from numerical studies, including simulation studies and real data analysis, demonstrate the promising empirical properties of the proposed approach, especially when the number of predictors is large. [ABSTRACT FROM AUTHOR]

A Special Section in the IEEE Transactions on Semiconductor Manufacturing, May 2014: After nearly three decades of research and development, wide band gap semiconductors (e.g. SiC and GaN) are ripe for high-volume applications in power electronics, communication, sensors, solid-state lighting, and photovoltaics. However, there are significant manufacturing challenges that must be overcome before large-scale manufacturing can take place. Fundamental issues pertaining to high defect density in the material, proper yield estimation and metrology techniques, and focus on "applications-driven" manufacturing are essential in order to advance the manufacturing of wide band gap (WBG) semiconductors. The IEEE Transactions on Semiconductor Manufacturing solicits original papers addressing the challenges and opportunities in manufacturing ofWBG semiconductor devices. Deadline for Receipt of Papers is July 31, 2013. [ABSTRACT FROM AUTHOR]