Marzieh Khakifirooz- Doctor of Philosophy Industrial Engineering and Engineering Management
- Professor (Assistant) at Tecnológico de Monterrey
Marzieh Khakifirooz
- Doctor of Philosophy Industrial Engineering and Engineering Management
- Professor (Assistant) at Tecnológico de Monterrey
Ai-driven decision making for Society 5.0
About
59
Publications
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Introduction
Marzieh Khakifirooz has a Ph.D. in Industrial Engineering and Engineering Management and an M.S. degree in Industrial Statistics from the National Tsing Hua University (NTHU), Hsinchu, Taiwan. Currently, she is an assistant professor at the Department of Industrial Engineering, Tecnológico de Monterrey, Mexico. She has outstanding practical experience from her various global consultancies for high-tech industries. Her research interests include the application of optimization in smart manufacturing, Industry 4.0, decision making, and machine teaching. She is an active member of System Dynamic Society, Institute of Electrical and Electronics Engineers (IEEE), and Institute of Industrial and Systems Engineers (IISE).
Skills and Expertise
Current institution
Additional affiliations
April 2014 - December 2014
Education
January 2015 - October 2018
Publications
Publications (59)
This paper introduces the Theory of AI-driven scheduling (TAIS), an innovative
framework designed to revolutionize service-oriented scheduling by integrating the
theory of constraints (TOC) (see APPENDIX I) with cutting-edge Artificial Intelligence (AI) technologies. TAIS extends the traditional five steps of TOC by
introducing three additional lay...
Airports are increasing their capacity to accelerate and facilitate travel and cargo delivery. At the same time, they aim to decrease expenses on delays caused by capacity overflow, encouraging policymakers to plan to enhance the capacity of crowded airports for the long term and set their transportation policies accordingly. This study develops a...
Supply chain (SC) resiliency and risk management have garnered increasing attention recently. While several studies have explored the use of scale-free network models to design and optimise SC networks, there remains a lack of a generalised stress-testing method that can be applied to various types and sizes of SCs. To address this, we propose a no...
Several developed vehicle spaces and time headway distribution models in traffic flow theory have been widely used in the literature, reflecting the primary uncertainty in drivers’ car-following movements and explaining the traffic flow stochastic features. Moreover, effective vehicle-to-vehicle (V2V) communication is a key to decentralizing traffi...
The literature on fatigue analysis can be classified into parametric or analytic
approaches that try to model the fatigue data with a specific distribution, such as
the optimal sequential Accelerated Life Test (ALT), considering the fatigue life cycle
and stress amplitude. To the best of our knowledge, no work incorporates the accel-
erated lifecyc...
In recent years, the adoption of statistical process monitoring (SPM) techniques in healthcare has been successful; for instance, biosurveillance and biosignal monitoring have found direct benefits. As the latest reviews of the literature show, parametric SPM techniques have been implemented to evaluate the quality-of-service hospitals provide, tra...
This study configures various carbon regulation mechanisms to control carbon emissions following clean technology strategies in engine oil production. Considering clean technology strategies for designing a sustainable supply chain (SSC) in the engine oil industry, two carbon reduction policies, namely, carbon capacity and carbon emissions tax, are...
Product return policies are widely utilized to increase customer security in retail markets. As a result, many retailers take various return leniency measures to ease the applicability of product returns for customers, which increases the frequency of returns in the market and has huge economic impacts on retailers. Therefore, it is necessary to ac...
This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processe...
This paper reports an integrated model for evaluating an early-stage third-party mobile application developer. By combining qualitative analyses, including Business Model Canvas (BMC), strengths, weaknesses, opportunities, threats analysis, and scenario planning, as well as quantitative analysis based on financial modeling and valuation, this study...
In this special issue, we call for rigorous research that borrows from various disciplines and presents relevant and original work related to the disruption of illicit markets using OR and analytics approaches. This can be rendered in various forms, such as a new way of framing the issue via problematization, design approaches and constraint induce...
The goal of this special issue is thus to improve the research and practice in issues related to analytics AI and OR solutions for social goods (AI&OR4SG) by mutually benefit from practitioners, researchers, and policymakers international collaborations; promoting the development of new methodology and metrics to address the specific challenges rel...
In recent years, the Public Bicycle Sharing System (PBSS) popularity for urban transportation is increasing. The fleet size of the system and the capacity of its stations are some key factors in establishing a successful sharing system. These factors affect the number of rejected demands and the lack of free docks for returning bicycles because of...
We consider a location-inventory optimization model for supply chain (SC) configuration. It includes a supplier, multiple distribution centers (DCs), and multiple retailers. Customer demand and replenishment lead time are considered to be stochastic. Two classes of customer orders, priority and ordinary, are assumed based on their demand. The goal...
We discuss issues related to the use of the normality assumption in statistical process monitoring with continuous data. Our illustrations involve the Shewhart X-chart. We illustrate some of the dangers and pitfalls in using nonlinear transformations in order to obtain the approximate normality of the process data. We argue that such transformation...
There is growing literature on new versions of “memory‐type” control charts, where deceptively good zero‐state average run‐length (ARL) performance is misleading. Using steady‐state run‐length analysis in combination with the conditional expected delay (CED) metric, we show that the increasingly discussed progressive mean (PM) and homogeneously wei...
![Linguistic variables for weighting criteria [34]](profile/Michel-Fathi/publication/350373519/figure/tbl1/AS:1005150437130240@1616657947118/Linguistic-variables-for-weighting-criteria-34_Q320.jpg)
Medication Errors (MEs) are still significant challenges, especially in nonautomated health systems. Qualitative studies are mostly used to identify the parameters involved in MEs. Failing to provide accurate information in expert-based decisions can provoke unrealistic results and inappropriate corrective actions eventually. However, mostly, some...
Advanced insurance companies move toward using advanced technologies such as telemat-ics to develop fair and transparent pay-as-you-drive (PAYD) automobile insurances. The expert service providers' opinions are essential and valuable for them to avoid and control any risk of entering a new market. Therefore, this study explores the critical factors...
The upsurge in atmospheric CO2 levels has come to humankind’s attention during the last couple of decades, mainly because the global temperature has risen, ice sheets have melted, and natural disasters have been happening more frequently and with more intensity. Hereby, the focus of this study is to develop a robust routing model that minimizes CO2...
The latest products and services have been designed and created under Sensing, Smart, and Sustainable (S3) and Industry 4.0 (I4.0) conceptualization. Moreover, there is a strong trend to develop more products using the S3 concept; on the other hand, I4.0 is the most advanced automation scheme implemented in manufacturing systems. Yet, a taxonomy th...
This work introduces a formation and variety of decision-making models based on operations research modeling and optimization techniques in smart manufacturing environments. Unlike traditional manufacturing, the goal of Smart manufacturing is to optimizing concept generation, production, and product transaction and enable flexibility in physical pr...
Ambient Intelligence (AmI) is built using sensors and actuators connected through real-time networks for smart systems. The data and signals captured from sensors are ambiguous for both human and machine. Artificial Intelligence (AI) is merged into an ambient environment to translate data and signals into a language understandable by human users an...
The upsurge in atmospheric CO2 levels has come to humankind's attention during the last couple of decades, mainly because of the rise in the global temperature, ice sheets melting, and more frequent and intense natural disasters. Hereby, the focus of this study is to develop a robust routing model that minimizes CO2 transportation emissions so that...
Traditional defect classification of TFT-LCD array processing leaned on human decision-maker in which visual inspection used to categorize defects and consequently identify the rout-causes of defects. In practice, the main sources of defects in the TFT-LCD array process are particles. Due to the huge size of the machinery and production tools in th...
Purpose-This study aims to explore the forthcoming trend of MS industry by examining its business model canvas and describing the business functions and role of the players in this industry. Design/methodology/approach-In order to discover the potential market, other than mining the academic paper, an in-depth interview method is implemented to gat...
The properties of a learning-based system are particularly relevant to the process study of the unknown behavior of a system or environment. In the semiconductor industry, there is regularly a partially observable system in which the entire state of the process is not directly or fully visible due to uncertainties or disturbances. The model for stu...
Scheduling under nonrenewable resources is one of the challenging issues in project scheduling problems. There are many cases where the projects are subject to some nonrenewable resources. In most of the literature, nonrenewable resources are assumed to be available in full amount at the beginning of the project. However, in practice, it is prevale...
The amount of time patients spends on services to be delivered in clinics, still is a major problem of some health centers. To solve this problem, various methods proposed by researchers. Failure Mode and Effects Analysis (FMEA) is one of the most used approaches to identify influential failure modes in prolongation of waiting time. In the FMEA met...
This study aims to develop a minimax game model for control design of overlay errors for semiconductor manufacturing. We highlight the main challenge in the control system of high-mixed wafer fabrication called overlay control. Indeed, the sophisticated and high-mixed setting is generated by multiple recipe adjustments for the scanner. The complexi...
Semiconductor manufacturing is a capital-intensive industry, in which matching the demand and capacity is the most important and challenging decision due to the long lead time for capacity expansion and shortening product life cycles of various demands. Most of the previous works focused on capacity investment strategy or product-mix planning based...
— It is vital to have an exclusive modification in semiconductor production process because of meeting differentiated customer demands in dynamic and competitive global
minuscule semiconductor technology market and the highly complex fabrication process. In this paper, we propose a control system based on the dynamic mixed-effect least-square suppo...
This chapter introduces a framework of disturbance rejection controller for discrete-time Run-to-Run (R2R) control system in semiconductor manufacturing environments. While we discussed the source of uncertainty and disturbance in wafer fabrication process, the photolithography process as one of the cutting-edge steps in wafer fabrication is select...
This study aims to develop a robust monitoring system for advanced control and compensation of the overlay errors based on ε -insensitive support vector regression (SVR), considering metrology delay. The proposed ε-insensitive SVR control system has the ability to solve quadratic optimization problems in real settings. To investigate the consistenc...
With advances in information and telecommunication technologies and data-enabled decision making, smart manufacturing can be an essential component of sustainable development. In the era of the smart world, semiconductor industry is one of the few global industries that are in a growth mode to smartness, due to worldwide demand. The important oppor...
The performance of reliability inference strongly depends on the modeling of the product’s lifetime distribution. Many products have complex lifetime distributions whose optimal settings are not easily found. Practitioners prefer to utilize simpler lifetime distribution to facilitate the data modeling process while knowing the true distribution. Th...
Advanced insurance companies are willing to use telematics to develop fair and transparent pay-as-you-drive (PAYD) automobile insurances. In Taiwan, the opinions of the expert service providers are essential and valuable for them to avoid and control any risk of entering the market. Therefore, this study aims to explore the key factors for introduc...
This volume provides resourceful thinking and insightful management solutions to
the many challenges that decision makers face in their predictions, preparations, and
implementations of the key elements that our societies and industries need to take
as they move toward digitalization and smartness. The discussions within the book
aim to uncover the...
Ambient Intelligence (AmI) refers to a networked environment of computing devices for implementing a "smart" system. AmI is built using sensors and actuators connected through real-time networks. The data and signals captured from sensors are ambiguous for both human and machine. Artificial Intelligence (AI) is merged into an ambient environment to...
Operations research and optimization in healthcare and disease modeling have received significant attention in the last three decades. This paper surveys several perspectives of operations research techniques in kidney disease, such as graph theory, queueing theory, Markov chain, and Phase-Type distribution (PTD). The kidney related problems includ...
In this book, theory of large scale optimization is introduced with case studies of real world problems and applications of structured mathematical modeling. The large
scale optimization methods are represented by various theories such as Benders’
decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig
–Wolfe decomposition...
Environmental issues like water, energy, and waste are necessitated organizations to understand that they are part of a more extensive system and their system needs to be radically transformed to respect to the society and guarantee the future of their business. More meticulously, the environmental issues would shape the future of the business. The...
A post-industrial revolution is encouraging the deployment of novel concepts both for designing smart factories and for creating a new generation of monitoring, control and man-machine collaboration systems. In general, companies are embracing an era of smart manufacturing built upon Cyber Physical Systems (CPS), the Internet of Things (IoT), and C...
Manufacturing in developed nations must incorporate more data capture and decision support to control costs and maintain product quality. Digital transformation of manufacturing means production must be transformed using technologies like robotics, Internet of Things (IoT), Intelligent systems, and real-time analytics. Smart manufacturing means all...
With advances in information and telecommunication technologies and data-enabled decision-making, smart manufacturing can be an essential component of sustainable development. In the era of the smart world, semiconductor industry is one of the few global industries that are in a growth mode to smartness, due to worldwide demand. The promising signi...
The multilayer overlay lithography process is one of the most challenging steps in wafer fabrication. In a multi-level manufacturing process, errors occur at each level and are accumulated in the upstream operations. Layer to layer error propagation, along with the stochastic bias, induce a sophisticated optimization problem and turns it into one o...
Shrinkage in semiconductor devices affects the process window of all wafer fabrication steps including plasma etching. Drifts or shifts are most significant effects on the etching process due to shrinkage in semiconductor devices. Any drift or shift affects on critical dimensions (CD) of the wafer and changes the thickness and the width over time....
Big data analytics have been employed to extract useful information and derive effective manufacturing intelligence for yield management in semiconductor manufacturing that is one of the most complex manufacturing processes due to tightly constrained production processes, reentrant process flows, sophisticated equipment, volatile demands, and compl...
The yield management in semiconductor manufacturing is one of interesting area that data mining approaches find useful applications. The abundant steps and complex workflows during wafer manufacturing automatically generate large volumes of data and, hence, engineers who rely on personal domain knowledge cannot find possible root cases of defects q...
Cleanroom monitoring is an ongoing process. Continuously monitoring the air quality ensures the filtration system is working properly and that no unknown particle generators exist. It is seldom useful to know how many particles are in a room; it is more useful to know if the room's contamination is increasing or decreasing over time. This is called...
The yield management in semiconductor manufacturing is one of the interesting areas that data mining approaches to find useful applications. The abundant steps and complex workflows during wafer manufacturing automatically generate large volumes of data and, hence, engineers who rely on personal domain knowledge cannot find possible root causes of...
Questions
Questions (3)
From Analytic Perspective, what is the main challenge /trend in asset pricing?
What you do if you have project, data subjects and no hand to run the project and no time to work on papers?
It is a widely known fact that academic publishing is a rigorous process. For many researchers, especially first timers, the publishing process can be a daunting task. Non-adherence to journal guidelines and publishing protocols result in outright rejections. Hence, the crude reality of academic publishing is that there are more manuscript rejections than acceptances, let alone successful publications. On the other hand, conducting research usually entails the benefits of employment and enhanced economic activity for the population as well. Reasonable availability of a safe and effective intervention may provide an important benefit for the population after the completion of some research trials. However, in many developing countries because of the lack of structural of ethical review, and lack of resources and expertise, there is less success for publication in well recognized journals, although the reputation and number of publications in these countries can compete with developed country.
We offer our free and unlimited support to researchers worldwide specially those who don’t access to commercial tools/services helping them to enhance the quality of their manuscript and to write a rigorous manuscript. Our team is include the experts in the fields of Operations Research, Industrial Engineering, Data Analytics and Statistical Inferences.
If you are needing our help, feel free to contact us.
my email: mkhakifirooz@tec.mx
