From all of us at AMC, we sincerely thank everyone who made it out to our inaugural Showcase on April 23, 2019 at University of Waterloo. We’re excited to report that the event was a huge success, with over 150 attendees and several great industrial project opportunities already reported.

Thank you to everyone who provided feedback. The survey is now closed. Your responses will contribute to even greater success at future events.

Missed out on the survey? We welcome additional feedback by phone (519-888-4567 ext. 37687) or by email.

Unable to attend? We’re sorry to have missed you! For those who weren’t able to join us, we encourage you to review the presentation materials and contact information below.

AMC thanks Executive Director Dr. Michael Worswick, Dean of Engineering Dr. Pearl Sullvian and Managing Director of AMC at Waterloo Harold Godwin for getting the day off to a great start with informative opening remarks.

An extra thank you to David Fransen of Next Generation Manufacturing Canada (NGen) and Craig McClelland of the Federal Economic Development Agency (FedDev) for highlighting other funding and partnership opportunities for Ontario manufacturers.

We are pleased to provide copies of the agenda, opening remarks and breakout session presentations:

Agenda for AMC Showcase April 23, 2019

Opening Remarks: AMC Overview, NGen, FedDev

Breakout Session: Multi-Scale Additive Manufacturing (MSAM) Laboratory

Breakout Session: Centre for Intelligent Antenna and Radio Systems (CIARS)

Breakout Session: WatCAR Manufacturing

Coming soon:

• Breakout Session: RoboHub

To learn more about each research group, please visit their respective home pages:

• MSAM
• CIARS
• RoboHub
• WatCAR Manufacturing

We also invite you to view the laboratory tour videos for the four research groups. 

https://youtu.be/gM9Jp9eLf1w

AMC is a provincially sponsored initiative that facilitates industry access to world-class facilities and research expertise.

Since AMC began in 2017, over 250 industry partners have partnered with Waterloo researchers on more than 100 projects.

The industry-focused research at Waterloo is undertaken by over 300 Highly Qualified People (HQP) in our four main areas. This breadth of expertise enables full collaboration with industry, scalability for projects of all sizes, with the confidentiality and rapid turnaround required by industry.

Get your project started with AMC today! AMC Engagement Information

Contact us today to learn more.

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Additive manufacturing (AM), also known as 3D printing, is revolutionizing manufacturing. While design and prototyping are common in fields such as medical, automotive, energy and aerospace, the full-scale manufacturing and distribution of AM parts is not yet reality due in part to complex quality control. The Multi-Scale Additive Manufacturing lab (MSAM) and Siemens Canada Limited (Siemens) partnered to create an innovative statistical tool that optimizes the process parameters of laser powder-bed fusion (LPBF), a class of metal AM process. The tool has the potential to benefit industrial suppliers and customers across the supply chain through improved and streamlined process optimization as well as cost savings. This project represents a significant research success and a great move toward realizing the full industrial potential of AM.

“Siemens welcomed the opportunity of working with the University of Waterloo based on the cutting-edge equipment available at MSAM. We have been very happy with the projects so far and anticipate this partnership will lead to future progress. “

– Dr. Ali Bonakdar, Advanced Manufacturing Technology Lead, Siemens Canada Limited

Siemens Canada Limited (Siemens) has been in operation for over 100 years, with over 4,500 employees in 39 offices and 14 production facilities across Canada. Siemens delivers innovative solutions for sustainable energy, intelligent infrastructure, finance, information technology, healthcare and manufacturing. In 2017, Siemens launched a collaborative AM Network to accelerate adoption of AM for design and production. Siemens provides both cash and in-kind support to MSAM in their highly productive relationship.

“Siemens is a pioneer of AM. Through this multi-faceted collaborative project, MSAM worked closely with a professional team of engineers to achieve highly innovative solutions for hurdles hindering the adoption of AM. The researchers involved have gained substantial experience in dealing with such a well-known companies. “

– Dr. Ehsan Toyserkani, Research Director, MSAM, University of Waterloo

Industrial AM applications include rapid prototyping, full-scale and spare part production, and rapid repair of existing components. As a digitized and customizable process, AM saves time and resources while increasing flexibility and scalability.
Despite the apparent advantages, full-scale deployment of AM to high-value components has been slow. Quality control is a major obstacle when the accuracy and consistency of critical properties (e.g., density, smoothness, mechanical strength, fatigue life etc.) are difficult to predict and control, particularly for metal AM where workflows comprise over 100 process parameters.
MSAM approached Siemens to discuss collaborative opportunities based on recent funding. This project began in July 2017 and focused on metal AM using LPBF. The challenge was to develop a commercially-viable approach to optimizing process parameters (e.g., laser power, printing speed, etc.).

Researchers developed a three-part statistical approach that optimized more than 20 LBPF parameters:

1. Determination of the most significant process parameters
2. Determination of the optimal input values to give reliable output
3. Validation of the approach

R&D was completed in only twelve months, and the resulting tool can be applied to LPBF applications using any powdered metal material source.
MSAM and Siemens have filed the patent to protect the methodologies and procedures. Representatives from Siemens global offices provided input throughout the collaborative process.

The statistical tool provides an estimated three-fold reduction in the number of printed test pieces required for understanding or optimization of printing parameters. This corresponds to an increase in part reliability, and saves costs by reducing time, effort, energy and materials.

Siemens plans to commercialize the tool in 2019 and anticipates the creation of engineering and/or sales positions.

The initial objective was optimization of density, hardness and surface roughness. Standard cube test pieces and artifacts were used for the process development and engine component prototypes were used for validation. Subsequent applications could use this approach to fine-tune the input parameters for other properties of interest (e.g., fatigue life or strength), and/or consider additional parts and materials.

AM opportunities are growing, and workflow optimization increases efficiency, customization and quality, translating to faster time-to-market and business growth.

Siemens will license and commercialize the workflow optimization tool as a service offered to their customers who rely on high quality AM part production.

Expanse Microtechnologies Inc. (Expanse) provides customized 3D x-ray computed tomography (CT) solutions to the additive manufacturing (AM) industry by bridging the gap between the complexity of CT data and the unique challenges in AM product and process development. This niche expertise blossomed from a close relationship with the Multi-Scale Additive Manufacturing (MSAM) group at the University of Waterloo (UWaterloo), where Expanse personnel provided training and analysis to MSAM in return for equipment usage and AM knowledge transfer.

“MSAM provided our team with encouragement and knowledge, helping us to become experts in a niche market while growing our business and capabilities.”

-James Hinebaugh, Ph.D., President, Expanse Microtechnologies Inc.

Expanse is an Ontario-based, virtually-operated company that provides customized material characterization services to the advanced materials and additive manufacturing (AM) industries, including medical, aerospace and automotive clients. Expanse was founded in 2016 as a result of a highly productive relationship with MSAM. The founders had significant experience with x-ray CT equipment, image processing and data analysis, and MSAM had a need for advanced analytical capabilities of their AM parts and materials. Expanse uses CT imaging and advanced data analytics to determine the properties of feedstock powders (e.g., porosity, morphology and distribution of particles and pores) and printed parts (e.g., surface texture, wall thickness, pore size and location, and dimensional metrology). Expanse also works with composite materials and developed a fiber isolation algorithm for use in advanced materials science. These critical analyses allow clients to leverage their equipment to improve products and processes. An example of the synergy between MSAM and Expanse is illustrated in the powder and product analytics developed by Expanse by leveraging competencies and equipment in the MSAM portfolio.

“Expanse Microtechnologies Inc. had an impressive transition from research collaborators to a successful start-up, while maintaining an excellent working relationship with UW. MSAM looks forward to continued collaboration as we expand our industrial R&D work.”

-Mihaela Vlasea. Ph.D., Associate Research Director and Assistant Professor, Multi-Scale Additive Manufacturing Lab, University of Waterloo

X-Ray CT is a non-destructive AM measurement tool that is well-recognized for its ability to illustrate voids and complex shapes not reliably measured with traditional methods. However, the complexity of CT machine operation and the detailed analysis of the resulting imagery are often barriers to AM researchers and not easily incorporated into product development. Similarly, CT machine experts are unfamiliar with the particular challenges and intricacies of AM materials and products. Prior to Expanse, there was no organization in Canada with the unique combination of advanced CT experience and AM knowledge. This competency gap was identified as a necessary hurdle to overcome so AM researchers and industry users could get the most value from their equipment.

The founders of Expanse developed an image processing algorithm to extract measurements from CT data that are most relevant to AM. Through collaboration with MSAM researchers, the algorithm was refined to address the quality and consistency of feedstock materials, AM equipment, and printed products.

Expanse trained MSAM researchers on CT equipment usage and provided valuable data analytics for MSAM projects. In return, MSAM provided Expanse with not only equipment access, but also invaluable AM knowledge and experience.

The knowledge exchange between Expanse and MSAM became a symbiotic relationship. As Expanse’s expertise and client base grew, MSAM leveraged their competency to become increasingly independent in CT use. Further, the collaboration provided enhanced data analytics to both teams that optimized part quality, equipment usage and research results, while Expanse continued to carve out a market niche.

Expanse grew from two employees in 2016 to six employees in 2018. They have developed prototypes with intricate AM features (e.g., overhangs, thin walls, intricate geometries) for prospective client demonstration. MSAM and Expanse continue to support each other in the integration of CT and advanced data analytics for optimizing AM products and processes.

Expanse expects to double its revenue in 2019 and increase staff by up to 50%. The company is working toward acquiring an Ontario-based facility with equipment complementary to MSAM’s, which will allow continued collaboration and growth.

The Precision Controls Laboratory at the University of Waterloo (UWaterloo), part of WatCAR Manufacturing, brings Industry 4.0 to life in conquering the complexity of gear manufacturing with an automated, virtual simulation tool that uses intelligent algorithms to optimize the machining of gears. UWaterloo developed virtual modelling software as a result of collaborative research with Ontario Drive & Gear (ODG) to increase production efficiency, improve gear quality, and reduce production costs, by eliminating much of the manual effort involved with traditional process development and quality control.

“The impact of our work with the Precision Controls Laboratory at UWaterloo has significantly increased productivity and decreased costs by enhancing the capabilities of ODG engineers.”

– Liam Tiernan, General Manager and Vice President, Gear Division, Ontario Drive & Gear

Founded in 1962, ODG operates from three facilities in New Hamburg, Ontario with 150,000 sq. ft. of manufacturing space. ODG designs, manufactures, assembles and tests over 1,000 unique gear and transmission products. Their diverse client base includes industrial, military, forestry, oil & gas, agricultural, automotive, and more. ODG has reported measurable productivity improvements and business growth as a direct result of collaboration with UW researchers.

The traditional approach to process development and quality control in gear manufacturing relies on technician experience, trial and error, and practical recommendations. These methods are expensive, tedious, and can also result in sub-optimal process parameters, wasted machine time and materials, or sometimes damage to tooling.

To overcome this challenge, UWaterloo researchers developed a virtual simulation of the physics of gear manufacturing, through in-depth mathematical analysis and intelligent algorithms, to represent the complex gear cutting mechanics, dynamic interactions between the CNC control system, the tooling and the workpiece. This enables process metrics and quality prediction to be achieved for ‘virtually machined’ gears.

A unique virtual machining program was developed and licensed by UWaterloo as a result of this collaborative research. The program requires input of dimensions, materials, tooling, machine/process parameters to employ a holistic approach to modelling the kinematics and dynamics of gear shaping. Process simulation and quality control in a virtual environment enables numerous iterations to optimize performance without wasting machine time and materials.

The software generates data and associated graphics that illustrate flaws and opportunities for optimization, and the integrated metrology allows the majority of the quality control to occur in a virtual simulation, thereby reducing process development time and cost.

In this successful technology transfer, UWaterloo researchers deployed the software at ODG, trained engineers and process developers on-site, and offer continued training support for current applications and future collaborative research.

ODG engineers and process developers were trained on-site by the UWaterloo team, resulting in successful technology transfer to fill the gap between scientific research and productivity on the shop floor.

ODG reported up to 24% production improvement for high-volume gear production for major Canadian customers, including a forestry equipment producer and a Tier 1 automotive supplier.

The reduction in production cycle times freed up machine capacity to grow the existing business and develop new customer relationships. This business growth has translated to a proportionate increase in shifts and hiring new manufacturing, quality control and support staff.

UWaterloo and ODG continue to collaborate on optimizing a broad suite of gear manufacturing operations (e.g., hobbing and power skiving), which is expected to result in additional cost savings, production efficiencies, improved part performance and business growth.

UWaterloo retains the software licensing and is eager to expand to new industry partners.