@article{latif_shao_starty_2020, title={A CASE STUDY OF DIGITAL TWIN FOR A MANUFACTURING PROCESS INVOLVING HUMAN INTERACTIONS}, ISSN={["0891-7736"]}, DOI={10.1109/WSC48552.2020.9383897}, abstractNote={Current algorithms, computations, and solutions that predict how humans will engage in smart manufacturing are insufficient for real-time activities. In this paper, a digital-twin implementation of a manual, manufacturing process is presented. This work (1) combines simulation with data from the physical world and (2) uses reinforcement learning to improve decision making on the shop floor. An adaptive simulation-based, digital twin is developed for a real manufacturing case. The digital twin demonstrates the improvement in predicting overall production output and solutions to existing problems.}, journal={2020 WINTER SIMULATION CONFERENCE (WSC)}, author={Latif, Hasan and Shao, Guodong and Starty, Binil}, year={2020}, pages={2659–2670} }
 @article{latif_shao_starly_2019, title={Integrating A Dynamic Simulator and Advanced Process Control using the OPC-UA Standard}, volume={34}, ISSN={["2351-9789"]}, DOI={10.1016/j.promfg.2019.06.200}, abstractNote={Insufficient interoperability has long been an issue on the factory floor, however, new technologies and standards are enabling production systems to become more agile and interoperable. A communication standard can, for example, make interoperation among different vendor-specific software and hardware tools in production systems easier and more reliable. In this paper, we share our research results and experience for the establishment of a connection between a dynamic simulator and an advanced process controller in a manufacturing system using OPC-UA. The OPC-UA communication protocol, which is middleware, acts as a common interface between these systems. We established the client and server for communication and defined an exchange data structure based on the OPC-UA standard for a control problem in a chemical process plant. The case study is a proof of concept of the OPC-UA standard implementation to support interoperability for different domains.}, journal={47TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE (NAMRC 47)}, author={Latif, Hasan and Shao, Guodong and Starly, Binil}, year={2019}, pages={813–819} }
 @article{shao_latif_martin-villalba_denno_2019, title={Standards-based integration of advanced process control and optimization}, volume={13}, ISSN={["2452-414X"]}, DOI={10.1016/j.jii.2018.10.001}, abstractNote={Integration of process control with optimization is critical to Smart Manufacturing (SM). Oftentimes, however, the process control solutions from one vendor do not interoperate with the optimization solutions of another. Incompatibilities among the representation and format used by the vendors can impede interoperability. Without this interoperability, it is impossible to achieve the higher level of decision support essential to SM. We believe that an emerging standard, ISO 15746, can facilitate semantic interoperability and enable the integration of process control with optimization. This paper reports the implementation and validation of ISO 15746, Automation systems and integration - Integration of advanced process control and optimization (APC-O) capabilities for manufacturing systems. Guided by the standard, we modelled major components of a typical APC-O system using tools from different vendors, implemented the information models defined in the standard, and integrated key system functions such as process optimization, process control, and user interface. A chemical process case based on the Tennessee-Eastman problem is used to demonstrate the implementation and validation of the standard. We developed a simulation of the chemical process and integrated it with the APC-O system. We discuss the standard validation experience and the findings will be used to guide advance development of the standard.}, journal={JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION}, author={Shao, Guodong and Latif, Hasan and Martin-Villalba, Carla and Denno, Peter}, year={2019}, month={Mar}, pages={1–12} }
 @article{latif_gopalakrishnan_nimbarte_currie_2017, title={Sustainability index development for manufacturing industry}, volume={24}, ISSN={["2213-1396"]}, DOI={10.1016/j.seta.2017.01.010}, abstractNote={Manufacturing industries are adopting new techniques and philosophies to address the acute shortage of non-renewable energy. Many of these manufacturing industries are focusing on achieving sustainability in every possible stage of their production, from raw material to the recycling of waste. Thus, the significance of using renewable energy, properly handling waste, and progressively conserving the environment is increasing day by day. In this research, the definition of sustainability is quite specific: being productive while making little to no impact on non-replenishable resources. The objective of the research is to determine the sustainability index of manufacturing plants. Since the topic has a broad scope, this research is limited to small and medium scale industries, which have common sets of operation and defined process plans. Besides, the focus is on non-hazardous waste and the indicators of the index are selected with respect to energy efficiency, workers’ health and safety and waste reduction potential. An interactive model has been developed to determine the sustainability index based on user responses. Based on the sustainable index, the model is able to provide suggestions to improve sustainability as well as carbon footprint reduction. The research has used datasets from various projects of the Industrial Assessment Center (IAC) at West Virginia University to build the knowledge database. The interactive model is validated by case studies from the IAC. The outcome of this research is a model that can assist industry to identify their shortcomings in achieving sustainability, determine the carbon footprint reduction potential, and compare the sustainability index as a benchmark measure.}, journal={SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS}, author={Latif, Hasan H. and Gopalakrishnan, Bhaskaran and Nimbarte, Ashish and Currie, Kenneth}, year={2017}, month={Dec}, pages={82–95} }