Motivation: The objective of this project is to implement CyManII technologies towards the secure digitalization of the composite thermal curing process of a small-to-medium manufacturer to improve energy efficiency through a cybersecurity playbook and program. 

Approach: Michigan Tech will lead the development of the cybersecurity playbook that includes Cyber-Informed Engineering (CIE) and Common Weakness Enumeration (CWE) tailored towards how to integrate an SMM’s supply chain within CyManII’s Secure Defensible Architecture (SDA) for Cyber-Physical Passport (CPP) deployment. This project is expected to demonstrate energy impact savings by preventing at least 9.09 GJ of wasted energy per month through secure digitalization of the SMM’s thermal curing line in addition to disseminating the results through the team’s network of over 2,800 small-to-medium manufacturers.

Partnerships: This work is sponsored by Cybersecurity Manufacturing Innovation Institute (CyManII) and is done in collaboration with Neuvokas, Corsha, Automation Alley, and the Society of Manufacturing Engineers.

Motivation: In floriculture, where the final product is the flowers themselves, a substantial portion of the process relies on manual labor to maintain product quality. However, the ongoing decline in agricultural labor poses a significant obstacle to the sustainability of operations. 

Approach: This project aims to develop a robotic platform by integrating advanced technologies, including mechanical design, artificial intelligence, modern control algorithms, and autonomous navigation, to address the labor shortage and offer cost-effective solutions to farmers. The platform will be tested for harvesting at Lucky Clover Farm in Gaylord, MI. Lucky Clover Farm boasts the cultivation of seven distinct lavender species, each exhibiting unique stem and flower morphology characteristics. .

Partnerships: This work is sponsored by the Michigan Department of Agriculture and Rural Development (MDARD) with Jung Yun Bae as the Principal Investigator .

Motivation: A significant barrier to adoption of digital manufacturing technologies is possible vulnerability of cyber infrastructure to malicious attacks. Thus, cybersecurity frameworks and standards have been developed by organizations including NIST, ISA, IEC and ISO. However, these standards are numerous and are vastly spread over the cybersecurity landscape, which is difficult for SMM’s to leverage these standards and frameworks.

Approach: This project aims to develop an accessible OT cybersecurity web portal to guide SMM’s towards adopting OT cybersecurity best practices. This portal will act as a one-stop-shop for SMM’s to survey the cybersecurity standards landscape in addition to viewing best practices. 

Partnerships: This work is sponsored by MxD and is done in collaboration with Calumet Electronics and MK Morse.

Motivation: Mobile robots, including autonomous cars, rely on a host of perception sensors to locally map their environments to supplement GNSS technology. However, evaluation of these maps are inherently difficult due to the unstructured nature of outdoor environments. Hence, there is a lack of evaluation technologies for automated driving sensor technologies.

Approach: This research aims to develop test methods to evaluate the construction of HD maps for mobile robot perception technology. These methods are systematically designed to evaluate camera, lidar, radar, and sensor fusion technologies.

Partnerships: This research is sponsored by the Autonomous Vehicles Working Group at NIST.