• Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks 

  Zhang, Nailong; Si, Wujun (Elsevier, 2020-11)

  Condition-Based Maintenance (CBM) planning for multi-component systems has been receiving increasing attention in recent years. Most existing research on CBM assumes that preventive maintenances should be conducted when ...

• Online monitoring and control of a cyber-physical manufacturing process under uncertainty 

  Nannapaneni, Saideep; Mahadevan, Sankaran; Dubey, Abhishek; Lee, Yung Tsun Tina (Springer, 2020-06-24)

  Recent technological advancements in computing, sensing and communication have led to the development of cyber-physical manufacturing processes, where a computing subsystem monitors the manufacturing process performance ...

• Design of response networks during disasters 

  Alsaadi, Ahmed K.; Krishnan, Krishna K.; Almaktoom, Abdulaziz T. (Institute of Industrial Engineers, 2020)

  Every year the world faces many different and diverse types of disasters. The effects of these catastrophes are vast and disastrous for humanity. These effects include economic devastation, massive structural damage, and ...

• Robust smart grid optimization based on wind energy 

  Alhamidi, Suliman A.; Chen, Zheng; Sawan, M. Edwin; Almaktoom, Abdulaziz T. (Institute of Industrial Engineers, 2020)

  Wind energy is commonly applied in the electrical industry and is fast developing all over the world. Attention has been focused on the reliable connection between a wind farm and the gas turbine. Many researchers hope to ...

• Defining multiple criteria for selecting an effective treatment plan for breast cancer 

  Hasan, Mostafa; Buyuktahtakin, Esra; Elamin, Elshami (Institute of Industrial Engineers, 2020)

  According to the American Cancer Society, 231,840 new cases were diagnosed with invasive breast cancer and approximately 40,290 women died in the United States in 2015. The selection of an effective treatment plan for ...

• Making the case for additive manufacturing: A review of cost models 

  Lamei, Zohreh (Wichita State University, 2020-05-01)

  Additive manufacturing (AM) is an emerging manufacturing method by which computer aided design models are directly made into products and structures. Layers of material, such as polymers, metals, ceramics, composites and ...

• Top administrators' perceptions of the quality in e-learning 

  Al Awadh, Mohammed (Wichita State University, 2020-05-01)

  INTRODUCTION: Many educational institutions around the world have adopted e-learning programs. The success of these programs depends on the availability of supporting technologies and the efficiency by which they are ...

• Probability of overlap 

  Jensen, Willis A.; Si, Wujun (Taylor and Francis, 2020-03-28)

  Consider a situation where we measure the strength of two different components that go into a finished product. In order for the product to work well, it is crucial that the strength of component A, not be greater than the ...

• Supervised machine learning approach for effective supplier classification 

  Harikrishnakumar, Ramkumar; Dand, Alok; Nannapaneni, Saideep; Krishnan, Krishna K. (IEEE, 2019-12)

  Supplier assessment plays a critical role in the supply chain management, which involves the flow of goods and services from the initial stage (raw material procurement) to the final stage (delivery). Supplier assessment ...

• Effect of carbon black silanization on isothermal curing kinetics of epoxy nanocomposites 

  Soltani, Seyed A.; Razinobakht, Seyed A.; Asmatulu, Ramazan (John Wiley and Sons, 2020-02-12)

  The present study was carried out to determine the effect of carbon black (CB) nanofiller silanization and loading on isothermal curing kinetics of epoxy nanocomposites. The epoxy resin specimens incorporated with 2, 4, ...

• Static test simulation of refill friction stir spot welded and riveted coupons using finite element analysis 

  Joseph Rosario, Gratias Fernandez (Wichita State University, 2019-12)

  Refill Friction stir spot welding (RFSSW) produces a solid-state lap joint between sheet metals, preferably aluminum alloys, without leaving behind an exit hole in the workpiece. This joining technique was derived from ...

• Digital twin based decision framework for jobshop layout production systems under disruptions 

  Vijayan, Vishakh (Wichita State University, 2019-12)

  In a hybrid layout production system under uncertainties, making strategic decisions becomes crucial and demanding with increase in complexity of the system. Advent of Industry 4.0 led to development of technologies such ...

• A reinforcement learning approach to industrial robotic operation 

  Thirumullaivoyal Santhana Kumar, Kaeshav (Wichita State University, 2019-12)

  In the current industrial market, all the companies strive to achieve shorter lead-times, reduced scrap and elimination of bottlenecks. To this regard, industries have recently employed human-robot teaming strategies in ...

• Event based dynamic multi-facility vehicle routing model 

  Madhu, Ajaykrishna (Wichita State University, 2019-12)

  The term 'Industry 4.0' mark the evolution of Information and Communication Technologies that promoted technological changes enabling modern supply chain logistics systems to work efficiently in a dynamic environment. ...

• Optimization methods for spatiotemporally fractionated radiotherapy planning 

  Adibi, Ali (Wichita State University, 2019-12)

  The goal in radiotherapy, as one of the main modalities for cancer treatment, is to deliver sufficient radiation dose to the tumor region to eradicate the disease while sparing the surrounding healthy tissues to the ...

• Optimization methods for tardiness/earliness scheduling problem in job shop environment 

  Kianpour, Parsa (Wichita State University, 2019-12)

  Motivated by the practical scheduling problem of job shops, this research aims to evaluate unrelated parallel machine scheduling problem with the objective of minimizing tardiness and earliness costs in both deterministic ...

• Real-time organ motion management in MRI-guided radiotherapy 

  Mirzapourrezaei, Seyedali (Wichita State University, 2019-12)

  Radiotherapy is one of the most commonly used modalities for cancer treatment. The goal of radiotherapy is to deliver a therapeutic dose of radiation to the clinical target volume while sparing the surrounding healthy ...

• Choosing radiology imaging modalities to meet patient needs with lower environmental impact 

  Alshqaqeeq, Fadhel Y.; McGuire, Charles W.; Overcash, Michael; Ali, Kamran; Twomey, Janet M. (Elsevier, 2020-04)

  Every patient that comes to Radiology has a different category of health problem. Based on diagnoses, each patient gets the appropriate imaging to aid in their treatment. The Healthier Hospital Initiative (HHI, ...

• Impact of commitment, information sharing, and information usage on supplier performance: a Bayesian belief network approach 

  Sener, Abdurrezzak; Barut, Mehmet; Dag, Ali; Yildirim, Mehmet Bayram (Springer Nature, 2019-12-19)

  Due to the proliferation of information systems and technology, supply chains have the capability of acquiring an enormous amount of supplier data in their databases. However, much of the useful supplier-specific insights ...

• Predictive model markup language (PMML) representation of Bayesian networks: an application in manufacturing 

  Nannapaneni, Saideep; Narayanan, Anantha; Ak, Ronay; Lechevalier, David; Sexton, Thurston; Mahadevan, Sankaran; Lee, Yung Tsun Tina (ASTM International, 2018-10-02)

  Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, ...

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