Innovation Projects Overview


CESMII Innovation Projects


Innovation Projects are Applications of the SM Platform that Create Profiles and Apps

The proposals selected for award negotiations represent a portfolio of projects that tightly align with the goals and metrics of the institute. The portfolio addresses use cases that span energy consumption, productivity, precision, performance, asset monitoring, and predictive maintenance. It contributes significantly to the creation of reusable information models and demonstrates extensive use of CESMII’s SM Innovation Platform. The portfolio will expand the Institute’s reach into industry verticals ( Food & Beverage, Marine, Warehousing, Automotive, Engines/Agriculture, Aerospace, Bio Manufacturing, Discrete Manufacturing/Small Medium Manufacturer-SMM), Garment, Hydraulics/SMM, Industrial Valves) and would bring in new members, most of them from the industry and the SMM community.

The teams selected for negotiation are listed below.

  • Case Western Reserve University (CWRU) and Rafter Equipment Corporation:
    Will create smart-manufacturing profiles for fault detection and predictive diagnostics for manufacturing tubes and pipes. The monitoring system can create reports that show potential areas of failure, recommend responses to maximize uptime and energy efficiency, and identify preventative maintenance needed to minimize unnecessary part replacement and maintenance tasks.
  • Atollogy, South Bay Solutions and North Carolina State University (NCSU):
    Will create smart-manufacturing profiles for Computer Numerical Control (CNC) machines to increase operational and energy efficiency for CNC machines at South Bay Solutions. This project presents an opportunity to both improve performance and leverage the data collected to establish a generic CNC Process Profile on the CESMII smart-manufacturing platform. The project team will use cameras and sensors for data collection, advanced machine vision and artificial intelligence edge processing. These advances will lead to better operational planning, scheduling and energy management.
  • Ectron will work with Inova Diagnostics:
    Will create smart-manufacturing profiles to improve their enzyme-linked immunosorbent assay (ELISA) process and production efficiencies applicable for pharmaceuticals, cosmetics and food industries. This project may effectively help measure antibodies, antigens, proteins and glycoproteins in biological samples during the pandemic.
  • Tyson Foods and ThinkIQ:
    Will create smart-manufacturing profiles to optimize yield and material utilization on Tyson’s poultry processing equipment, enabling decisions based on real-time constraints in material flows, manufacturing operations, and energy consumption in a protein-based food processing environment. This project will demonstrate increased operational efficiencies that could be extended to other food processing and energy-intensive industries.
  • ECM Performance Materials Corp and Flexware Innovation:
    Will create smart-manufacturing profiles to improve throughput, quality and energy efficiency across ECM’s chemical mixing and packing production lines. The project will provide a framework that small-to-medium-sized manufacturers can use to reduce collection, parsing and real-time data storage costs
  • G-W Process Optimization, Nutrition Bar Confectioners (NBC) and Central NY Tech Development Organization:
    Will develop a solution to improve cooling tunnel performance, product quality and energy consumption at NBCy creating reusable structured information models (SM Profiles) and a data driven predictive model demonstrated with the SM Innovation Platform.  With an anticipated throughput increase of 10% and a decreased need for rework of 12%, the energy cost/bar will go down significantly.
  • Oregon State University and Ectron Corporation:
    Will develop a solution to improve energy consumption and productivity of the hop drying process for four facilities in the Pacific Northwest by obtaining real-time data, creating reusable structured information models (SM Profiles) and a data driven predictive model to optimize operating parameters and improve energy consumption.  The project estimates that they can save 1-1.5 hours in total time from the long drying time of 6-11 hours, and thus saving energy and time.
  • Brunswick Corporation and Concurrency:
    Will develop and demonstrate a machine learning based forecasting model for supply chain fulfilment and inventory optimization for engines and boats, using a reusable structured information model (SM Profile) based on data from demand planning systems and manufacturing operation.
  • Concurrency and Clover Imaging:
    Will use an AI based cognitive bot service to provide audio-visual instructions to workers with cognitive disabilities in a warehouse environment, combined with part location and identification information in a structured information model (SM Profile) for a warehouse application, demonstrated in the SM Innovation Platform environment.
  • GE Digital and J.M. Smucker:
    Will use the capabilities of the SM Innovation Platform to create and demonstrate an SM Profile based standard interface to synchronize product data in Product Lifecycle Management/Enterprise Resource Planning (PLM/ERP) with operations data in Manufacturing Execution Systems (MES)  systems, resulting in improved real-time decision making during disruptive business conditions.
  • Adapdix and Tesla:
    Will demonstrate a pre-configured, adaptive Station AI edge controller to improve uptime and yield by predicting and optimizing robotic cell performance during vehicle manufacturing, enabled by a structured information model (SM Profile) for real-time data collection on performance parameters, anomaly detection and cell operation data.
  • Toward Zero and Raytheon:
    Will develop and demonstrate a cost-effective connectivity solution for legacy machines (that need to be upgraded for sensors and connectivity) by integrating an  on-premise machine connectivity device (edge device), the SM Innovation Platform and structured information models (SM Profiles) including sensor and operational data, to improve operational efficiency, quality and predictive maintenance by at least 5-10% at four facilities.
  • Caterpillar:
    Will develop and demonstrate a data driven predictive model for reducing energy usage via early detection of engine test failures, enabled by data collection and contextualization in the SM Innovation Platform through a structured information model (SM Profile) for the test bed.  The project estimates that they can improve the ability to predict success / failure of engine test with greater than 85% confidence from the current 70%.
  • Rensselaer Polytechnic, Penn State University and Janssen/Johnson & Johnson:
    Will develop a model-based control solution for process and quality improvements in manufacture of monoclonal antibody (mAb) -based drugs, enabled by structured information model (SM Profiles), SM Innovation Platform based data contextualization, data driven algorithms for predicting morphology and a feed-forward scheme to control the process.  The project aims to understand how much they can improve purification process for improving the quality of mAb.
  • Advanced Manufacturing International:
    Will work with several partners and small manufacturers to demonstrate a cost-effective SM solution based on affordable on-premise machine connectivity device (edge hardware), SM Innovation Platform and structured information model (SM Profiles) to lower the cost for adopting smart manufacturing technologies at three small manufacturers of chemicals, furniture and precision manufacturing.  This project will help in understanding and reducing  the potential bottlenecks for SMMs in terms of  cost of adopting smart manufacturing technologies.
  • Fifth Generation Technologies (5G) will partner with Wipro :
    Will demonstrate how improvements can be made through use of SM technologies use cases for hydraulic component manufacturing by utilizing pre-built software applications and data access through the SM Innovation Platform and structured information models (SM Profiles) for Wipro’s assets.
  • Litmus Automation and Bray International:
    Will develop and demonstrate a monitoring and anomaly detection solution to improve throughput, reduce waste, and reduce scrap in industrial valve manufacturing by integrating an on-premise machine connectivity device (edge device), the SM Innovation Platform, structured information models (SM Profiles) and anomaly detection.
  • Commonwealth Center for Advanced Manufacturing, Association for Manufacturing Technology and Beeond:
    Will develop tools for automatic generation of SM Profiles using OPC-UA-MTConnect companion specifications with the SM Innovation Platform, to enable rapid population of the SM Marketplace with SM Profiles for common MTConnect and OPC-UA compliant machines. This project will help CESMII in meeting one of their objective of helping manufacturers to rapidly adopt smart manufacturing technologies and reduce the cost of deployment.
  • Interface Technologies, Hickey-Freeman, Rensselaer Polytechnic and CGS, Inc:
    Will develop a structured information model (SM Profile), integrated with the SM Innovation Platform to connect robotic sewing work cell with existing shop floor control systems, and create an application for automated labor reporting to help improve productivity in apparel manufacturing.  The project estimates that both the SM Profile and the application will lower integration costs to increase adoption of the robotic system which itself targets a 30-50% increase in sewing operator productivity.


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