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Marine Photovoltaics – An IoT-Integrated Approach to Enhance Efficiency
Published in Rupendra Kumar Pachauri, Jitendra Kumar Pandey, Abhishek Sharma, Om Prakash Nautiyal, Mangey Ram, Applied Soft Computing and Embedded System Applications in Solar Energy, 2021
R. Raajiv Menon, Jitendra Kumar Pandey, R. Vijaya Kumar
The maintenance issues experienced in floating energy farms are often obviated by the IOT technology. The IOT often utilizes a real-time Supervisory Control And Data Acquisition (SCADA) network (Baker et al., 2020; Hunzinger, 2017; Sajid, Abbas, & Saleem, 2016; Shahzad, Kim, & Elgamoudi, 2017) to monitor the power generation and equipment condition of the floating farm (“Can Floating Solar Plants Break Free from the Trappings of High Maintenance?,” n.d.). These systems are configured to undertake routine maintenance checks and initiate built-in self-checks whenever a malfunction occurs (“What Is SCADA? Supervisory Control and Data Acquisition,” n.d.). The system, upon sensing a malfunction, generates an alarm signal in addition to initiation of maintenance check. The process can be remotely monitored by the customer or by the intermediate maintenance team. These IOT-based systems are put into use in order to undertake smart decisions with supported data analysis and, thus, mitigate system downtime. IOT-based solar farms have shown results in saving significant amount of time and money.
Modular Approaches in Biomass and Waste Industries
Published in Yatish T. Shah, Modular Systems for Energy and Fuel Recovery and Conversion, 2019
Consequently, energy consumption and costs can be significantly reduced by employing the right equipment. Siemens uses “smart motor control centers” (MCCs) that not only save energy and help the environment, but also decrease the cost of producing ethanol. Integrating motor control data into the SIMATIC PCS 7 process control system provides users with the information that they need to understand and optimize their energy usage. Smart MCC integration helps to [24]: Improve productivity by monitoring motor operating conditions.Reduce installation, commissioning, and maintenance project phase costs.Minimize downtime through predictive maintenance.Minimize the total cost of ownership.
The Economics of Semiconductor Scaling
Published in Lambrechts Wynand, Sinha Saurabh, Abdallah Jassem, Prinsloo Jaco, Extending Moore’s Law through Advanced Semiconductor Design and Processing Techniques, 2018
Lambrechts Wynand, Sinha Saurabh, Prinsloo Jaco, Abdallah Jassem
A typical manufacturing process can consist of up to 700 individual process steps with a total manufacturing time of up to three months. While the main focus of semiconductor manufacturers in the past was on delivering a good product, the sheer scale and costs involved in modern manufacturing processes necessitated an approach of optimizing and utilizing manufacturing equipment in the best possible manner in order to keep the manufacturing processes cost-effective (Mönch et al. 2013). One aspect that is of particular concern to semiconductor manufacturers is the downtime of manufacturing equipment and machinery; downtime refers to a time period where equipment cannot participate in production. Downtime is typically due either to scheduled maintenance or to an automatic shutdown event caused by the equipment performance degrading beyond limits specified by the production engineers.
Manufacturing productivity analysis by applying overall equipment effectiveness metric in a pharmaceutical industry
Published in Cogent Engineering, 2021
Muhammad Zubair, Shahid Maqsood, Tufail Habib, Qazi Muhammad Usman Jan, Uroosa Nadir, Muhammad Waseem, Qazi Muhammad Yaseen
An effective way of minimizing system downtime and corresponding maintenance costs is to determine an optimal maintenance strategy (Daneshkhah et al., 2017). Corrective maintenance (CM) and preventive maintenance (PM) are the two widely used maintenance strategies. It is very challenging to identify an optimal preventive maintenance decision that targets the best balance between these types of maintenance and which tends to minimize the overall maintenance costs.