Soundar Kumara

Pennsylvania State University | Penn State · Department of Industrial and Manufacturing Engineering

The automotive industry has used in-line conveyor systems to move vehicles through the general assembly process since the early days of vehicle manufacturing in the 20th century. With products shifting to EVs (Electric Vehicle) and the emergence of AMRs (Autonomous Mobile Robot), there is an opportunity to transform the assembly process into a more...

The cold sintering process (CSP) is a low-temperature consolidation method used to fabricate materials and their composites by applying transient solvents and external pressure. In this mechano-chemical process, the local dissolution, solvent evaporation, and supersaturation of the solute lead to “solution-precipitation” for consolidating various m...

Metal additive manufacturing (MAM) offers a larger design space with greater manufacturability than traditional manufacturing has offered. Despite continued advances, MAM processes still face huge uncertainty, resulting in variable part quality. Real-time sensing for MAM processing helps quantify uncertainty by detecting build failure and process a...

In this research, a theoretic physics-based framework for identification of defects via analysis of strain fields is presented. This framework comprises identification of self-similarity of strain fields followed by their dimensionality reduction using kernel based principal component analysis. The efficacy of this framework is tested qualitatively...

Healthcare experts have come to a consensus that effective and safe vaccines are necessary to control the rapid spread of the ongoing COVID-19 pandemic across the globe. Since the traditional vaccine development and manufacturing approaches were unable to meet the rapidly growing COVID-19 vaccine demand, biopharmaceutical firms had to devise novel...

Additive manufacturing (AM) provides a higher level of flexibility to build customized products with complex geometries, by selectively melting and solidifying metal powders. However, wide applications of AM beyond rapid prototyping are currently limited by its ability to perform quality assurance and control. Advanced melt-pool monitoring provides...

Suicide is a growing public health concern in the United States. A detailed understanding and prediction of suicide patterns can significantly boost targeted suicide control and prevention efforts. In this article we look at the suicide trends and geographical distribution of suicides and then develop a machine learning based US county-level suicid...

In a high‐mix and low‐volume manufacturing facility, heterogeneous jobs introduce frequent reconfiguration of machines which increases the chance of unplanned machine breakdowns. As machines are often nonidentical and their performance degrades over time, it is critical to consider the heterogeneity and non‐stationarity of the machines during sched...

We propose a method to identify inequity in access to emergency services using logistic regression and present a model to address inequity by siting additional facilities, recommending both quantity and location. We classify emergencies by the median income bracket of their Zip code tabulation areas. We use logisitic regression to determine whether...

When maintenance resources in a manufacturing system are limited, a challenge arises in determining how to allocate these resources among multiple competing maintenance jobs. We formulate this problem as an online prioritization problem using a Markov decision process (MDP) to model the system behavior and Monte Carlo tree search (MCTS) to seek opt...

Healthcare experts have come to a consensus that effective and safe vaccines are necessary to control the rapid spread of the ongoing COVID-19 pandemic across the globe. Since the traditional vaccine development and manufacturing approaches were unable to meet the rapidly growing COVID-19 vaccine demand, biopharmaceutical firms had to devise novel...

Biopharmaceutical community is devising modern techniques to boost the development, production, and distribution of COVID-19 vaccines in large scale with tremendous speed. This has shifted the focus towards smart manufacturing of vaccines through vaccine platforms. Vaccine platforms have great potential to rapidly generate new vaccines and can over...

Biopharmaceutical community is devising modern techniques to boost the development, production, and distribution of COVID-19 vaccines in large scale with tremendous speed. This has shifted the focus towards smart manufacturing of vaccines through vaccine platforms. Vaccine platforms have great potential to rapidly generate new vaccines and can over...

Biopharmaceutical community is devising modern techniques to boost the development, production, and distribution of COVID-19 vaccines in large scale with tremendous speed. This has shifted the focus towards smart manufacturing of vaccines through vaccine platforms. Vaccine platforms have great potential to rapidly generate new vaccines and can over...

As the Coronavirus Disease 2019 (COVID-19) pandemic continues to grow globally, testing to detect COVID-19 and isolating individuals who test positive remains the primary strategy for preventing community spread of the disease. Therefore, automatic and accurate detection of COVID-19 using medical imaging modalities, which are more widely available...

Additive manufacturing (AM) is a layer-by-layer material deposition process that allows for more manufacturing flexibility and design complexity than traditional manufacturing processes. However, the print quality in metal AM is hard to be predicted and controlled due to its high process variability. Numerous process parameters are correlated/inter...

With rapid advances in internet and computing technologies, sharing economy paves a new way for people to "share" assets and services with others that disrupts traditional business models across the world. Specifically, rapid growth of additive manufacturing (AM) enables individuals and small manufacturers to own machines and share under-utilized r...

In 2020, California required San Francisco to consider equity in access to resources such as housing, transportation, and emergency services as it re-opened its economy post-pandemic. Using a public dataset maintained by the San Francisco Fire Department of every call received related to emergency response from January 2003 to April 2021, we calcul...

Metal additive manufacturing (MAM) provides a larger design space with accompanying manufacturability than traditional manufacturing. Recently, much research has focused on simulating the MAM process with regards to part geometry, porosity, and microstructure properties. Despite continued advances, MAM processes have many variables that are not wel...

Often in manufacturing systems, scenarios arise where the demand for maintenance exceeds the capacity of maintenance resources. This results in the problem of allocating the limited resources among machines competing for them. This maintenance scheduling problem can be formulated as a Markov decision process (MDP) with the goal of finding the optim...

Additive manufacturing (AM) enables the creation of complex geometries that are difficult to realize using conventional manufacturing techniques. Advanced sensing is increasingly being used to improve AM processes, and installing different sensors onto AM systems has yielded more data-rich environments. Transforming data into useful information and...

Advances in low cost and reliable sensing, connectivity (Internet of Things), computational power, and advanced analytics, are leading to a new wave of innovation in machinery status sensing and condition monitoring. Significant research efforts are directed towards cloud computing architectures. However, given the latency, bandwidth, cost, securit...

Patient satisfaction is a key performance indicator of patient-centered care and hospital reimbursement. To discover the major factors that affect patient experiences is considered as an effective way to formulate corrective actions. A patient during his/her healthcare journey interacts with multiple health professionals across different service un...

Quality is a key determinant in deploying new processes, products or services, and influences the adoption of emerging manufacturing technologies. The advent of additive manufacturing (AM) as a manufacturing process has the potential to revolutionize a host of enterprise-related functions from production to supply chain. The unprecedented level of...

As the Coronavirus Disease 2019 (COVID-19) pandemic continues to grow globally, testing to detect COVID-19 and isolating individuals who test positive remains to be the primary strategy for preventing community spread of the disease. The current gold standard method of testing for COVID-19 is the reverse transcription polymerase chain reaction (RT-...

Advanced manufacturing is moving towards a new paradigm of ‘low-volume-high-mix’ production. There is an urgent need to develop effective representations of real-world 3D objects and further enable the matching and retrieval of engineering designs. This paper presents a new self-organizing network representation of 3D objects. Each voxel of the 3D...

BACKGROUND The rapid spread of COVID-19 means that government and health services providers have little time to plan and design effective response policies. It is therefore important to rapidly provide accurate predictions of how vulnerable geographic regions such as counties are to the spread. OBJECTIVE To develop county level prediction around n...

Background: The rapid spread of COVID-19 means that government and health services providers have little time to plan and design effective response policies. It is therefore important to quickly provide accurate predictions of how vulnerable geographic regions such as counties are to the spread. Objective: To develop county level prediction arou...

Key Points: Question: What are key factors that define the vulnerability of counties in the US to cases of the COVID-19 virus? Findings: In this epidemiological study based on publicly available data, we develop a model that predicts vulnerability to COVID-19 for each US county in terms of likelihood of going from no documented cases to at least on...

This paper presents a systematic methodology to enable environmental sustainability and productivity performance assessment for integrated process and operation plans at the machine cell level of a manufacturing system. This approach determines optimal process and operation plans from a range of possible alternatives that satisfy the objectives and...

Nonlinear dynamical systems often generate significant amounts of observational data such as time series, as well as high-dimensional spatial data. To delineate recurrence dynamics in the spatial data, prior efforts either extended the recurrence plot, which is a widely used tool for time series, to a four-dimensional hyperspace or utilized the net...

Identifying drug-drug interactions (DDIs) is a critical enabler for reducing adverse drug events and improving patient safety. Generating proper DDI alerts during prescribing workflow has the potential to prevent DDI-related adverse events. However, the implementation of DDI alerting system remains a challenge as users are experiencing alert overlo...

This study aims at developing SuperOrder, an order recommendation system for outpatient clinics. Using the electronic health record data available at midnight, SuperOrder predicts the order contents for each upcoming appointment on a daily basis. A two-level prediction framework is proposed. At the base-level, the predictions are produced by aggreg...

A Do-It-Yourself (DIY) framework of part design and manufacturing is proposed. This framework relies on a digitally indexed part/process-plan library that can enable amateur fabricators in designing and manufacturing complex shapes with similar tolerance as professional counterparts. A methodology to do this is proposed, which involves automated id...

Recent advances in sensors and other streaming data sources of plant floor automation and information systems open an exciting possibility to predict the risks of faults and breakdowns across a manufacturing plant over much longer time horizons than what is conceivable today. This paper introduces a Manufacturing System-wide Balanced Random Surviva...

The modern manufacturing industry is investing in new technologies such as the Internet of Things (IoT), big data analytics, cloud computing and cybersecurity to cope with system complexity, increase information visibility, improve production performance, and gain competitive advantages in the global market. These advances are rapidly enabling a ne...

Many real-word systems exhibit nonlinear and nonstationary dynamics, which defy understanding based on the traditional reductionist's approach. However, traditional analytical methods designed to effectively handle nonlinear dynamics are not well integrated with multi-sensor data fusion for process monitoring and control objectives. Realizing full...

Community structure points to structural patterns and reflects organizational or functional associations of networks. In real networks, each node usually contains multiple attributes representing the node?s characteristics. It is difficult to identify the dominant attributes, which have definitive effects on community formation. In this paper, we o...

Condition-based maintenance involves monitoring the degrading health of machines in a manufacturing system and scheduling maintenance to avoid costly unplanned failures. As compared with preventive maintenance, which maintains machines on a set schedule based on time or run time of a machine, condition-based maintenance attempts to minimize the num...

Nonlinear dynamical systems exhibit complex recurrence behaviors. Recurrence plot is widely used to graphically represent the patterns of recurrence dynamics and further facilitates the quantification of recurrence patterns, namely, recurrence quantification analysis. However, traditional recurrence methods tend to be limited in their ability to ha...

Surface finishing processes consume 20–70% of the cycle time of the emerging additive manufacturing process chains. Effective representations of the spatiotemporal evolution of the surface morphology are imperative towards developing monitoring schemes to arrest cycle time overruns. We present a thermodynamically consistent random planar graph repr...

Rapid advancement in sensing, communication, and mobile technologies brings a new wave of Industrial Internet of Things (IIoT). IIoT integrates a large number of sensors for smart and connected monitoring of machine conditions. Sensor observations contain rich information on operational signatures of machines, thereby providing a great opportunity...

The emergence of cloud computing, industrial internet of things (IIoT), and new machine learning techniques have shown the potential to advance prognostics and health management (PHM) in smart manufacturing. While model-based PHM techniques provide insight into the progression of faults in mechanical components, certain assumptions on the underlyin...

An important part of the engineering design process is prototyping, where designers build and test their designs. This process is typically iterative, time consuming, and manual in nature. For a given task, there are multiple objects that can be used, each with different time units associated with accomplishing the task. Current methods for reducin...

Manufacturers have faced an increasing need for the development of predictive models that help predict mechanical failures and remaining useful life of a manufacturing system or its system components. Model-based or physics-based prognostics develops mathematical models based on physical laws or probability distributions, while an in-depth physical...

Manufacturers have faced an increasing need for the development of predictive models that predict mechanical failures and the remaining useful life (RUL) of manufacturing systems or components. Classical model-based or physics-based prognostics often require an in-depth physical understanding of the system of interest to develop closed-form mathema...

The present study examined the surface integrity of open cell aluminium foams at full volume using X-ray micro-computed tomography. The structural network was reconstructed in voxel models, for which watershed segmentation and medial axis extraction was utilized to identify interconnected pore (air) and strut (solid) phases. From these models, post...

This paper proposes a classification scheme for performance metrics for smart manufacturing systems. The discussion focuses on three such metrics: agility, asset utilization, and sustainability. For each of these metrics, we discuss classification themes, which we then use to develop a generalized classification scheme. In addition to the themes, w...

Introduction: The authors of this work propose an unsupervised machine learning model that has the ability to identify real-world latent infectious diseases by mining social media data. In this study, a latent infectious disease is defined as a communicable disease that has not yet been formalized by national public health institutes and explicitl...

One of the most significant advances in the development of computer science, information and communication technologies is represented by the cyber-physical systems (CPS). They are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at...

Additive manufacturing (AM) is a promising technology that is expected to revolutionize industry by allowing the production of almost any shape directly from a 3D model. In metal-based AM, numerous process parameters are highly interconnected, and their interconnections are not yet understood. Understanding this interconnectivity is the first step...

1*2 Additive manufacturing (AM) is a promising technology that is expected to revolutionize industry by allowing the production of almost any shape directly from a 3D model. In metal-based AM, numerous process parameters are highly interconnected, and their interconnections are not yet understood. Understanding this interconnectivity is the first s...

Sustainable manufacturing, smart manufacturing, and green manufacturing are some of the contemporary phrases used to promote economic, social, and environmental improvements in the logistics and manufacturing sectors. Text analytic techniques were used to automatically extract, summarize, and cluster keyphrases from thousands of literature articles...

Background: Transitional care interventions can be utilized to reduce post-hospital discharge adverse events (AEs). However, no methodology exists to effectively identify high-risk patients of any disease across multiple hospital sites and patient populations for short-term postdischarge AEs. Objectives: To develop and validate a 3-day (72 h) AE...

Studying the Nanomaterial Environmental Impact NEI is a critical task in nano-health and safety. However, there is a lack of visual analytic tools that can efficiently query and present large-scale bibliography metadata, NEI characterisations and nanomaterial toxicity. This paper presents the user-centred design and implementation efforts of develo...

Modern manufacturing systems are installed with smart devices such as sensors that monitor system performance and collect data to manage uncertainties in their operations. However, multiple parameters and variables affect system performance, making it impossible for a human to make informed decisions without systematic methodologies and tools. Furt...