List
Development of a Predictive Maintenance System for Motors at Tate & Lyle
Wo Jae Lee
Tate and Lyle, a WHIN manufacturer, currently uses manual vibration analysis techniques as part of their predictive maintenance program. WHIN researchers with Tate & Lyle's assistance have installed commercial vibration sensors in their facility on five test motors in parallel to their once-a-month manual data collection methods. From these efforts Purdue researchers hope to develop predictive analytics techniques from our live wireless sensors to someday replace T&L's manual labor intensive methods with semi-automated real time predictive maintenance methods.
Predictive Maintenance on Rotating Systems Using Artificial Neural Networks
Haiyue Wu, Hanjun Kim, and Byung Gun Joung
As part of WHIN, Purdue researchers are perfecting methods to detect rotating system failures in manufacturing applications. To better predict future failures, neural networks are being used to recognize data patterns to detect such failures as bearing failures in motors and furthermore to be used in any type of rotating operations to detect bearing failures. A mini-testbed has been created to simulate normal and failure modes of motors to assist this research.
MTConnect-Based Smart Manufacturing Framework and Its Application
Huitaek Yun
MTConnect is a common communication method for internet machine connections. Standard MTConnect communication is one way only, machine to Internet device. Purdue researchers have established two-way communication using a modified communication platform opening vast opportunities for smart manufacturing concepts to be utilized on the next-generation manufacturing floor.
IoT for Ag Testbed at ACRE
Dennis Buckmaster, Bruce Erickson, and John Scott
One of the main objectives of WHIN is the development of Testbeds. Purdue plans on developing their main Agricultural Testbed at ACRE. This poster gives an overview of the main aspects, elements, and near term plans of that testbed. All WHIN testbeds are to be used to inform, educate, and demonstrate current IoT technologies, while also acting as a proving ground site for emerging near future technologies.
Education for Digital Agriculture
Bruce Erickson
This poster highlights the proposed educational offerings planned by Purdue University as part of the Digital Agricultural segment of the WHIN project. The poster covers high school, undergraduate, and graduate level studies, along with Professional level offerings.
UAV: WHIN Region Select Case Studies
John Scott
This poster highlights some of the 2018 WHIN region Drone application case studies. Case studies included on this poster include Drone use for field scouting purposes, studies on turf trends for turf management applications, Cover crop interseeding studies, transmission tower inspection, and soil compaction damage around a tower installation, and projections for 2019 activities.
An Open-Source Infrastructure for Real-Time Automatic Agricultural Machine Data Processing
Y. Wang, S. Noel, J. Krogmeier, and D. Buckmaster
Biosensor for in-situ Measurement of Microbial Activity in Soil
Jose Waimin
As the negative impacts of heavy pesticides and fertilizers have upon the environment continue to be understood, we will need to look for alternative practices. Monitoring microbial activity in soils cost effectively with future sensors will be a key to the development of these alternative practices. This poster highlight possibilities being studied/development along these lines.
Flexible Nitrate Sensors: Uses in Aqueous Environments and Implementation of LoRa Wireless Communication System
Jose Waimin
With Purdue's efforts to development low cost Nitrate sensor, methods for deployment and communications must be established, this poster describes developments underway to defining those deployment methods and the LoRa Wireless communication setups and data management techniques possible.
Manufacturing Methods for Low-Cost Agricultural Chemical Sensors
Nicholas Glassmaker, Siamak Shams Es-Haghi, Guy Telesnicki, Armen Yildirim, and Miko Cakmak
This poster highlights the planned manufacturing methods to product low cost chemical sensors, including soil nitrate sensors for Agricultural use.
Roll-to-Roll Printed Nitrate Sensor for Agricultural Application
Hongjie Jiang, Jose Fernando Waimin, Siamak Shams Es-haghi, Armen Yildirim, Mukerrem Cakmak, Rahim Rahimi, and Babak Ziaie
Low cost Nitrate sensors are not commercially available. WHIN researchers are developing printed Nitrate sensors which will be low cost and able to be easily mass produced. WHIN hopes to make these sensors easily available to WHIN region farmers.
Predictive Design, Performance and Robustness Analysis of R2R Nitrate Sensor
Xin Jin, Hongjie Jiang, Rahim Rahimi, Fnu Chandra Mouli Sekar, Bruno Ribeiro, Babak Ziaie, and Muhammad A. Alam
The development of physics-based models will allow thin film nitrate sensor performance to be analyzed, predictive, and robust to meet the commercial needs of farmers. This poster highlights those efforts and activities.
Physics-Reinforced Deep Learning for Fast Chemical Sensing
S Chandra Mouli, Bruno Ribeiro
Newly deployed chemical sensors being developed can take a long time to saturate to establish sensor readings. Using Physics deep learning models might provide a solution to accurately predict future sensor readings using just a few initial hours of the readings. This poster is an overview of this research activities for WHIN
Increasing Life-Expectancy: Energy Optimization in a Sensor Network through In-Sensor-Analytics and Collaborative Intelligence
Dong-Hyun Seo, Baibhab Chatterjee and Shreyas Sen
When considering battery power as a main power source for IoT devices; energy consumption and battery life are critical parameters. This poster highlights WHIN researchers efforts to optimize sensor power sources by using multiple methods and techniques.
Image-Based Quality Assurance of Inkjet Printed Electronics and Coated Screen Printed Electronics
Qingyu Yang, Yang Yan, Kerry Maize, Professor Allebach, Professor Shakouri
As the Purdue WHIN team develops low cost printed sensors using mass production methods; the need arises for establish quality assurance standards for these future products. This poster describes some of the ongoing activities to establish those standards and the relationships between sensor quality and performance.
Reliable Mesh IoT Network and Data Analytics
Heng Zhang, Xiaofan Jiang, Mustafa Abdallah, Nithin Raghunathan, and Saurabh Bagchi
WHIN Supply Chain Leakage
Mihir Bhatia, Deepika Jindal, Anesh Krishna , Nachiket Joshi, and Hemant Devavarapu
WHIN has identified that 85% of all OEM outsourcing activities are spent outside of the region. One of the main contributor to this is manufacturer's difficulty in finding qualified local firms. Purdue's Krannert school of management team is developing a supply chain tool which companies from the region can use to find local sources and reduce this leakage.
