Chemical Analysis Testing Now Available at Industrial Technology Centre

The Industrial Technology Centre is pleased to announce a new addition to our services – Chemical Analysis.

Material Qualification

It is important for materials to meet regulatory, performance and quality requirements. Chemical analysis of ferrous material helps ensure your products meet these requirements. ITC’s chemical analysis service can help you identify unknown alloys and characterize materials.

Our Resources

ITC uses a Bruker Q4 TASMAN Advanced CCD Based Optical Emission Spectrometer (OES) for analysis.

With a measurement range from sub-ppm to percentage levels, we can characterize your materials from trace analysis in pure metals to high alloyed grades.

Optical emission spectroscopy allows all elements in your sample to be analyzed simultaneously, ensuring fast turn-around on your results. A high-energy arc is applied to the sample, causing it to emit spectra that identify the elements present. The amplitude of the spectra allow the instrument to measure the proportions of each element.

Analysis Capabilities
● Carbon steel
● Stainless steel
● Cast iron

Applications
● Metal production
● Metal processing
● Manufacturing
● Recycling

For further information about this new capability, call 204.480.3333 or send email to tech@itc.mb.ca.

The Connected Factory

What is a connected factory? It is an array of innovations that impact a consolidated, connected and flexible model of organizing factory operations. These improvements primarily relate to the ability of machines to efficiently communicate with each other, the integrated flow of data to a centralized platform, and cross-device functionality. In the past, a human was required to be on the factory floor. Now, the employees, who are responsible for monitoring and controlling production lines, can do so remotely.

The control that can be employed from remote consoles is often comprehensive, comprising a large arrangement of functions, from output level control to repair and maintenance.

Factories can now adapt to workflows in real time, by machines communicating with other machines, and humans. This system brings together people, processes and products to enable continuous delivery of value to a company’s customers.

By connecting all of the parts of the manufacturing process, a manufacturer can simplify and speed up the process of building and testing applications across every platform. Supervisors can monitor the health, performance, and utilization of all applications, workloads, and infrastructure. Business intelligence will grow by making better, faster decisions by analyzing data for deeper insights as to what is happening on the factory floor.

The connected factory can seamlessly integrate applications, data, and processes across both on-premises and the cloud. No matter where data resides, costly business interruptions can be avoided by protecting both data and applications. During an outage or disaster scenario, a disaster recovery solution will protect a range of applications, enabling an entire datacenter to be recovered in a matter of hours instead of weeks or months.

Using a common platform, equipment connected by sensors can supply helpful data about the continuing condition of equipment. This information can be analyzed to predict potential locations of equipment breakdown and production shutdown. In the event a breakdown does occur, a factory can analyze this data to determine the problem and take corrective actions to prevent future occurrences.

Using the IoT (Internet of Things), a manufacturer can connect devices, assets, and sensors to collect untapped data. This also allows a company to deliver scalable, reliable applications faster to meet the ever-changing demands of its customers. A company can focus quicker on innovation instead of infrastructure management.

Good communications between people and production equipment means that transitions among areas go according to plan and process design. Poor or no communication leads to inefficiencies and quality problems. When production equipment talks to other production equipment, it makes manufacturing flow efficiently. This is IoT in action.

New levels of productivity can be found in the connected factory, because of machine-to-machine integration and the Industrial Internet of Things, making the connected factory intelligent and aware. This incorporates using sensors rather than human decision to fine tune the operation of the machinery, using data from the production machinery to adjust workflows, which eliminates inefficient procedures, capacity attrition, wastefulness and performance bottlenecks. This is accomplished by remotely tracking, monitoring and adjusting machinery based on sensor data from different parts of the factory.

Inventory represents a substantial cost for most manufacturers, and an IoT approach can reduce excess inventory through automated replenishment. The production equipment on the factory floor can communicate when quantities are low and order more raw materials to safeguard against the line shutting down, utilizing just-in-time, cost-effective replenishment.

In order to boost manufacturing, new machines, processes and organization can be tied together thanks to the emergence of the Internet of Things and the wide spread of connectivity in the factories. Along with the IoT, human/robot teamwork, virtual reality and 3D manufacturing comprise the future of manufacturing.

This means that all industrial assets will be connected within the same factory as well as between factories. Sensors at each stage of production will exchange data in real time which will then be analyzed to guarantee the ideal operation.

Previously, robots used in factories were designed to work alone and perform single tasks. In the future, we will see more Cobots (collaborative robots), which are intelligent robots designed to work with production people in order to accomplish more with less effort.

Management can utilize virtual reality to design and simulate a product from its creation to finished product. Not only can virtual reality design and simulate a product it can also design the entire production facility, including equipment positioning, employee movement and a simulation of procedures. VR can then test the entire production from start to finish.

3D printing (manufacturing) uses only the material that is strictly necessary to build a product, eliminating the waste that we see when products are built by eliminating material. The 3D printer is controlled by a computer, depositing successive layers until they reach the desired final shape. This approach will make it possible to design lighter, more complex, and lower cost products while obtaining a substantial reduction in the industry’s ecological footprint.

These milling machines, as well as similar arrays of injection molding presses and 3D printers, are connected to the Proto Labs network. Data collected by sensors track the progress of orders and help optimize scheduling. The monitor seen on the left displays real-time updates. Image courtesy of Proto Labs Inc.

General Motors Co. has connected about a quarter of its 30,000 factory robots to the internet, and GM is realizing less down time. In the last two years, GM has avoided 100 potential failures of vehicle assembling robots by analyzing data that the robots sent to external servers in the cloud. Connectivity is inhibiting assembly line interruptions and robot replacements that can take as long as eight hours. Connecting robots to the internet for preventive maintenance is just the beginning of a surge of new robotics technology; and GM is using robots that can work safely alongside humans in the factory.

Siemens’ PLC manufacturing plant in Amberg, Germany has automated the production of its automation systems. The result is a reported 99.99885 percent perfect production quality rate. This is impressive given the plant produces around 12 million Simatic PLCs each year.

At Tesla’s Gigafactory in Nevada, mobile robots called Automated Guided Vehicles or AGVs are being used for moving items from one point to another. Besides the AGVs, the Gigafactory is also equipped with robotic arms that assist humans in making the battery packs at the plant.

Bosch GmbH has put the connected factory at the center of the company’s strategy. Bosch makes an array of smart consumer products, and is the world’s leading manufacturer of Micro-Electro-Mechanical Systems sensors, and provides a host of components for automotive manufacturers. Bosch has achieved a 25 percent output improvement for its automatic braking system and electronic stability program production with the introduction of smart, connected lines.

Bosch has pushed to remake the company’s 250 factories around the world using connected technology. The most advanced plant is in Homburg, Germany, which makes hydraulic components for cars. Connected technologies have enabled that plant to increase productivity by 10% and reduce inventory by the way of faster turnover by 30%.

The core tools needed to implement a connected factory already exist, such as sensors, controllers, big data, the Internet of Things, and cloud computing. More than a technological revolution, the connected factory is a total reorganization of the approach to production, using existing tools and placing a greater reliance on networks.

For additional information:

  1. http://ignition.altran.com/wp-content/uploads/2017/03/factory-of-the-future-towards-zero-downtime.pdf
  2. https://www2.deloitte.com/content/dam/insights/us/articles/4051_The-smart-factory/DUP_The-smart-factory.pdf
  3. http://www.iec.ch/whitepaper/pdf/iecWP-futurefactory-LR-en.pdf
  4. https://www.intel.com/content/dam/www/public/us/en/documents/white-papers/factory-of-the-future-vision-2030.pdf

>> Read more by Len Calderone, Manufacturing Tomorrow, 1/09/18

Module Combines Multiple Sensors in a Tiny Package

A new module from TE Connectivity promises to simplify the development of smart electronic products by incorporating multiple sensors in a package that’s smaller than the head of a match.

Known as the multi-sensor module, the new product can include up to four sensors and a microprocessor, and can transmit data from the sensors through a single set of wires. As a result, it creates a smaller footprint and less mass for applications where minimal size and weight are paramount. At the same time, it reportedly reduces development complexity.

“Design engineers don’t have to figure out a way to mount it on a circuit board, power it up, or develop software to talk to it,” Pete Smith, senior manager for sensor product knowledge and training at TE Connectivity, told Design News. “We do all that for them.”

TE Connectivity’s multi-sensor modules can incorporate multiple sensors in a package measuring 5 mm X 3 mm X 1 mm. (Source: TE Connectivity)

The module can incorporate sensors for measurement of temperature, humidity, pressure, fluid viscosity, fluid density, and dielectric constants, among others. One of the company’s multi-sensor modules includes a temperature sensor, altimeter, and humidity sensor, along with a microcontroller, in a package measuring just 5 mm X 3 mm X 1 mm, Smith said.

Early applications of the technology include an automotive windshield module that monitors temperature and humidity, and an automotive engine module that measures barometric pressure, temperature, and humidity in a car’s intake manifold. The windshield application enables a vehicle’s climate system to determine if the glass is about to fog up. The engine application allows the ECU to adjust the fuel injectors to maintain the best air-fuel mixture. The company is also working on medical applications that monitor air quality for respirators, ventilators and incubators.

Additional potential applications include smartphones, tablet PCs, HVAC systems and weather stations.

Smith said that the product was inspired by the demands of customers. “They wanted to combine sensing capabilities into single packages that would provide advantages for developing new products,” he told us. Those advantages include reduced size and weight, as well as simplified wiring. Analog signals from the sensors are digitized and transmitted from a microprocessor or microcontroller through a single set of wires, he said. The technology also provides a logistical advantage because it reduces inventory and eliminates the need for users to deal with multiple suppliers.

TE Connectivity is able to offer multi-sensor packages because it has the advantage of manufacturing many different types of sensors, Smith said. At least 12 different types of the company’s sensors are available for use in the modules, he added.

TE’s multi-sensor strategy comes at a time when many IoT developers are moving electronic intelligence out to the so-called “edge” of their applications. A package that includes multiple sensors and a microcontroller could be a good fit for such applications because it promotes simplicity, Smith said.

“An engineer can take one of these sensor modules, plug it into a board, download the software and have it up and running in a half-hour,” he said. “Whereas, with a boxful of separate sensors, it could take weeks.”

>> Read more by Charles Murray, Design News, December 1, 2017

 

Impending Changes to Trademark Law: Why You Should Consider Registering Yours Sooner Rather than Later

The Government of Canada has been overhauling Canada’s trademark laws in an effort to modernize its intellectual property (IP) framework.

The Trade-marks Act has been updated with some notable amendments. Many were hoping that these amendments would be addressed in the regulations. However, with the first draft of the updated regulations now released, it appears cause for concern remains.

Under the current system, anyone who files a trademark application must provide a date of first use or a declaration of use with respect to their trademark prior to registration, unless they are relying on the registration and use abroad basis which is not common.

The amendments to the Trade-marks Act have eliminated the pre-registration statement of use requirement. The first draft of the regulations, released by the Government of Canada on June 19, 2017, does not address the issue. Thus, it appears under the new system that a person may file a trademark application without any declaration or statement regarding use. This change in the use requirement has caused significant concern about an uprising of “trademark trolls”: those who register a trademark in an effort to prevent legitimate registrations, or to sell the trademark at an inflated price to the businesses that would be entitled to the trademark but were not fast enough or aware of the impending changes to trademark law.

Another change on its way is the classification of the goods and services associated with a trademark that need to be described in a trademark application. Currently, goods and services need only be described in ordinary commercial terms in a trademark application. In order to comply with the Nice Agreement, an international treaty being adopted by Canada pursuant to the amendments to the Trade-marks Act, a trademark applicant will be required to include the classes under which the goods and services fall within the Nice Classification System. The current system, which includes a $250 online filing fee regardless of the number of classes listed in the application, may be replaced with a $330 filing fee for the first class together with $100 for each additional class listed in the trademark application. On average, a trademark application has at least 3 classes.

With the weakening standards for who can obtain a trademark and the potential increase in cost, businesses would do well to consider registering their trademarks before the new laws come into force. The Canadian Intellectual Property Office is predicting that the new amendments to the Trade-marks Act and regulations will come into effect early 2019.


DISCLAIMER
This article is presented for informational purposes only. The content does not constitute legal advice or solicitation and does not create a solicitor client relationship. The views expressed are solely the authors’ and should not be attributed to any other party, including Thompson Dorfman Sweatman LLP (TDS), its affiliate companies or its clients. The authors make no guarantees regarding the accuracy or adequacy of the information contained herein or linked to via this article.

The authors are not able to provide free legal advice. If you are seeking advice on specific matters, please contact Keith LaBossiere, CEO & Managing Partner at kdl@tdslaw.com, or 204.934.2587. Please be aware that any unsolicited information sent to the author(s) cannot be considered to be solicitor-client privileged.

While care is taken to ensure the accuracy for the purposes stated, before relying upon these articles, you should seek and be guided by legal advice based on your specific circumstances. We would be pleased to provide you with our assistance on any of the issues raised in these articles.


Our thanks to author Silvia de Sousa, of Thompson Dorfman Sweatman LLP, for sharing this information with our readers.

Silvia’s practice is concentrated in the area of business law with an emphasis on intellectual property law, life sciences law and technology law.

North America Takes Lead in Industry 5.0 by Necessity

Reposted from RoboticsTomorrow.com by Matt Rendall on June 15, 2017

Something has changed in the last 10 years – while manufacturers have focused on continuous improvement within their space, the technology sector has also been making leaps and bounds in innovation, with new capabilities spanning cloud computing, big data, and mobile computing. These two independent, yet innovative industries, have now come to a pivotal moment: they are converging and the United States is uniquely positioned to take full advantage of these developments and redefine what it means to incorporate robotics on the factory floor.

For American manufacturers, robotics and automation is no stranger. They have studied and put into practice the Ford Production System and the Toyota Production System to continuously improve operations, with much of those improvements made by the use and integration of automation. As such, the sector has traditionally been one of the first industries to grab hold of burgeoning robotics technologies and incorporate them into process.

However, the convergence of advanced technology and manufacturing processes requires an organizational leader. Someone who will research, advise, and embrace on capability and process that were nothing more than imaginative a decade ago. This leader will drive robotics and automation solutions on the factory floor, and at the same time incorporate process, design and key strategies. This leader will emerge as the Chief Robotics Officer (CRO).

 

The CRO will lead Industry 5.0

The ‘CRO’ is a concept fueled from the progression of Industry 4.0. Also stemming from the ‘next industrial revolution’ as it is so often thought of are technologies spanning IoT, cloud computing, and big data – all of which play a critical role in the development of industry. Yet, something within the notion of CRO holds a certain level of integrity. Why? Because this role will not only lead the research and development initiatives for Industry 4.0 integration within the factory floor, it will leverage existing strategies to launch Industry 5.0.

In the last decade, Industry 4.0 capabilities have emerged through burgeoning technology, arguably attributed to accelerated changes in the market from ecommerce to requirements for mixed model production – the customer needs and wants are ever changing. The notion is characterized by Big Data and the Industrial Internet of Things to connect process through technologies and generate data. While these copious data are useful, even actionable if reported and leveraged properly, it is Industry 5.0 that ensures manufacturing leadership is focused and design methodologies to improve facility operations and manufacturing strategies across North America while addressing ways to overcome the key challenges facing industry today.

Realizing that education must occur to build the bridge from Industry 4.0 to 5.0, Drive Manufacturing Summit is the first conference to embrace this line of thought. This unconventional conference will facilitate conversation around the cultural shift, not just informing attendees of advancements, but educating them on how to integrate them into their facilities for future proofing. It will change the entire manufacturing sector and the imperative to move beyond Industry 4.0 to Industry 5.0.

While Germany lead the conversation of Industry 4.0 with its introduction in 2011 as the 4th industrial revolution, North America is uniquely positioned to lead the next, through industry 5.0. The Fourth Industrial Revolution, or Industry 4.0,  was first referenced by the German Federal Ministry of Education and research began to explore the various trends that were taking place. They wanted to identify things in high level technology that could help to improve the world and boost technology. This would allow those seeking future employment in the industrial sector to have a simplified work experience while allowing us to do more in a fraction of the time.  By 2012, the Germans had collected a great deal of research and they used this information to hold the first presentation on the subject. They took the smart factory setting and showcased some of the potential of Industry 4.0, allowing potential customers and industry professionals to gain a deeper understanding of what all was possible.

The operational impact of Industry 4.0 was the high-level concept that machines could think; reacting, and creating functional improvement to boost efficiencies and Overall Equipment Effectiveness (OEE). The German government was thrilled with the results and they began to boost funding to the research in the hopes it would advance their country and help them to become a frontrunner during the Industrial Revolution.

And now, 2017, Industry 5.0 is on the horizon; it will be North America to head the race.

A study on future global competitiveness, by Deloitte Global and the U.S. Council on Competitiveness, predicted that the U.S. will dislodge China as the most competitive manufacturing nation in the world in 2020.

“Manufacturing competitiveness, increasingly propelled by advanced technologies, is converging the digital and physical worlds, within and beyond the factory to both customers and suppliers, creating a highly responsive, innovative, and competitive global manufacturing landscape,” said Craig Giffi, a leader in Deloitte US Consumer & Industrial Products Industry group and co-author of the report.

There is a unique personality to the North American manufacture: a no-nonsense “get the job done” philosophy.  Industry 4.0 brought about new technologies and capabilities, but failed to address 90% of manufacturers real-world, day-to-day challenges.  Step in, step up:  Industry 5.0.

North America, once the global leader in manufacturing acquiesced to Japan in the 1970s – 1990s; then China as a world manufacturing leader.

Why NA is positioned to lead the way

So, why will North America step forward now to lead the way? because we must. The Economist reported that the USA is close to full-employment with just a 4.3 percent unemployment rate.

https://lh3.googleusercontent.com/ORldcyd3OHW3ID9YmOvUVD_FuYGU0EobuT147L11vOhtW7Dhohl83kL-PDEvgiFQhOS0Ez6mxVRfzC1rDqvVBBOQQQs9SFcJGSGfrAJv8PBMz438j2wnbEI0J_FtCBvuXVeH2W09

Source: US Bureau of Labor Statistics

But even with excellent employment rates, the manufacturing sector suffers from retention, disinterest from millennials and, most notably, a significant skills gap.

Manufacturers have reported a sizeable gap between the talent they need to keep growing their businesses and the talent they can actually find for nearly a decade; now it is a dire situation. Beyond today’s talent issues though, manufacturers need to address skills gaps for future years. The trajectory of the skills gap over the next decade according to Deloitte and The Manufacturing Institute embarked on their Skills Gap study, seeking to answer these pressing challenges The report reveals the issue is growing and is exacerbated by a number of factors that brings manufacturers to an inflection point that must be addressed in order to ensure viability and success of American-based operations as well as the nation’s economic prosperity as a whole.

Robotic solutions are not a panacea.  Fears of displacing workers are deeply exaggerated; this skills gaps highlights the error in thinking among those who have long seen robotics and automation as job stealers. Industry 5.0 is a manufacturer’s integration of automation as the needed skill workforce is absent requiring the role of automation as a very attractive and feasible option.

Machines do not replace human workers and create job losses to improve productivity. Rather, the lack of qualified human workers has driven the conversation to Industry 5.0, the implementation of robotic systems, which result in greater productivity. A 4.3 percent unemployment rate is something to celebrate yet more than five million North American manufacturing jobs that remain unfilled. And without the required skillsets, both robots and automation systems will remain in strong demand.

The significant skills gap is deeply exacerbated by those preparing to retire also threaten a manufacturer’s ability to attract and attain human workers. As baby boomers are leaving the workforce in massive numbers, 10,000 per day; an estimated 2.7 million jobs applicants will be needed due to these retirements.

Furthermore, wages are increasing drastically. This change is enough in itself to fuel the rise of Industry 5.0.

Source: US Bureau of Labor Statistics

 

Until now, even at full employment, hourly wage earnings have been slowly creeping up.  That is about to change. In 2017, over 20 states are slated to increase minimum wage with California leading the way. They plan to increase minimum wage annually until 2022, bringing the minimum wage rate to $15.00 per hour.  Wage increases leave manufacturers in a dilemma: increase wages for all employees and be forced to either raise prices on manufactured goods or products, or cut into profits.

The combination of increasing hourly wages, a skills shortage, and the threat of a retiring workforce are at the intersection of automation and manufacturing excellence.  It is the intersection known from this day forward as Industry 5.0, which will be carefully and strategically incorporate into business operations by the Chief Robotics Officer.

http://www.roboticstomorrow.com/article/2017/06/north-america-takes-lead-in-industry-50-by-necessity/10198

Pallets + Robots = a Competitive Advantage?

Palletizing is a trending application for collaborative robots. Could it give a competitive edge to your business? Robotiq looks at the history of pallets and their importance for modern logistics.

Packaging is one of top applications for collaborative robots. Unsurprisingly, pallets are a huge part of this. Many small businesses send and receive goods on pallets. The job of loading and unloading is repetitive, boring and ergonomically risky. Robots are an obvious solution.

Pallets have revolutionized global logistics. Since the 1920’s they have played a significant role in the world economy. They have had huge impacts on product design, from IKEA mugs to children’s books. It’s common for products to be redesigned to fit more units onto one pallet.

Pallets were born around the 1920’s, coinciding with the invention of the forklift truck. This was no coincidence. Forklifts suddenly provided a way to transport heavy loads around the warehouse. Pallets made it quick and easy to lift high volumes of product and stack them on top of each other.

Up until the 1950s, pallets were still loaded manually. When mechanical palletizers finally came on the scene, humans hands were suddenly freed from the repetitive, physical work of loading and unloading.

When industrial robots appeared, it wasn’t long until they were being used for palletizing. The first robotic palletizer was introduced by Fuji Yusoki Kogyo in 1963.  Suddenly, palletization could be as almost as flexible as a human worker.

Robots palletizers had many advantages over their mechanical predecessors:

  • They are inherently reprogrammable.
  • They often take up less space.
  • They can easily handle many different product types.
  • They can do mixed-case palletizing.
(Robotiq.com)

With the rise of collaborative robots, the transition from human hands to robot hands is complete. Unlike previous robot palletizers, which used large industrial robots, collaborative robots are accessible to even the smallest of businesses.

Pallets themselves are now ubiquitous, but it’s now especially important how you handle them. Businesses can differentiate themselves by improving the palletization and depalletization of products from these pallets.

Robotic packaging and distribution is becoming increasingly important thanks to the popularity of ecommerce and distributed supply chains. Small businesses need to be able to scale their order fulfillment quickly without incurring extra expenses or introducing delays in the orders.

(Robotiq.com)

Currently, only 20% of logistics warehouses use automation. However, this looks likely to increase. A recent DHL trend report showed that robot usage in logistics is rising. It suggested that cobots are more effective than non-collaborative robots when it comes to the needs of logistics.

Distribution of products can be a deciding factor in the scalability of a business. Warehousing has the potential to provide a competitive advantage to those businesses that can use it effectively, and robotics is becoming a key tool for doing that.

In an article from Food Logistics, supply chain consultant Tony Vercillo explained why automation can help businesses to thrive in the modern climate:

“The trick to warehousing is eliminating human touches. Every time a human touches a pallet or a case, an expense occurs. Technology should be used to reduce the number of touches and steps within the warehouse process.”

Collaborative robot palletizing can bring these advantages within the reach of small businesses. We don’t all need to have fully-automated warehouses like Amazon does to benefit from automated packaging.

>> Read more by Alex Owen-Hill, Robotiq, April 18, 2017

5 Augmented Reality Suppliers to Watch in 2017

With growing interest in Internet of Things (IoT) applications more and more companies are seeking AR as an enterprise solution to make visual use of the massive amounts of incoming data.

In a report released this month, ABI Research predicts that AR will hit an inflection point in 2018 and grow to a $98 billion market by 2021, with energy, manufacturing, and logistics verticals accounting for the largest market shares.

Here are some of the top companies worth watching in the years ahead:

  1. Scope AR

Headquartered in Canada, Scope AR focuses on AR for creating “smart instructions” and live video support calling solutions. The company’s goal is to leverage AR to make the jobs of technicians and workers, both in the factory and on the field, simpler.

Back in November, the company announced a partnership with Caterpillar to provide live support for Caterpillar dealers in repairing, troubleshooting, and maintaining equipment. Scope AR’s Remote VR technology uses an AR headset (like Microsoft Hololens) or even a tablet or smartphone to overlay annotations, 3D models, and contextual cues onto live video, while also allowing for live audio and video connection. Essentially a field technician could connect to someone on-site for real-time support.

Scope AR has also recently unveiled its WorkLink software, which allows companies to create their own AR-based smart instructions for a variety of tasks from installation to maintenance. The platform requires no coding experience and smart instructions can be created in a manner of hours without the need for a separate team or outsourcing.

2. OPS Solutions

Michigan-based OPS Solutions is bringing AR into manufacturing assembly, training, inspection, and quality control with its Light Guide Systems (LGS). The LGS is a system that overlays interactive projections onto any object placed underneath it. The projections provide cues, instructions, and even error checking and the system is capable of recognizing objects and the user’s hand movements in order to ensure tasks are being completed correctly.

The LGS can guide a worker through a task step by step as it’s being performed and eliminate the need for printed work instructions or computer screens and can also ensure workers do not miss key steps in an assembly or maintenance process.

The company has also recently announced a partnership with Hewlett Packard on its Light Guide Pro System, a more compact version that runs on a HP Sprout Pro PC and is targeted at office, hospital, and home use.

3. Drain

Canada-based Ngrain is aiming to be an enabler for AR applications. Company’s Producer Pro software is an automated platform for managing, producing, and deploying AR experiences without the need for coding or 3D graphics experience. Customers can create content for maintenance and assembly applications and upload it to a mobile app.

The company’s name comes from the idea of treating models as though they are made of grains of sand. Ngrain’s software utilizes a proprietary engine captures numerous, granular 3D data points of an object (voxels, the 3D equivalent of pixels) in order to create a detailed, 3D model that can then be delivered via the software. From there users can use AR glasses, tablet, or other wearable display to examine a virtual simulation of the object in a real-time environment.

https://youtu.be/jc0eugBFauk

4. Vuzix

On the hardware end, Vuzix has become the new AR company on everyone’s mind. With Google Glass shelved and the Microsoft’s Hololens still building up momentum, customers are still waiting for a headset to do for AR what the Oculus Rift and HTC Vive have done for virtual reality (VR).

After a successful showing of its M3000 smart glasses at CES 2017, the company is expected to roll out its enterprise smart glass product in summer of 2017. The M3000 is meant to be an AR headset for enterprise and commercial applications, targeted at industrial, medical, supply chain, retail, and help desk applications (i.e. those being created by other suppliers on this list). At the M3000’s core is an Intel Atom processor and 64GB of built-in memory. The headset also features a camera for live streaming and recording as well as wireless connectivity capabilities that allow it to interface with Android and iOs devices. It also features head tracking, GPS, as well as voice control and gesture controls (via a touch pad).

5. ESI Group

While not an AR-based company, what makes French company ESI Group interesting is that it is tackling the same issues many AR suppliers are looking at, but doing so with VR.

ESI Group’s focus is on what the company calls, “immersive virtual engineering,” combining immersive VR with virtual prototyping . The latest version of their software IC.IDO (pronounced “I See, I Do”) adds support for head-mounted displays (HMDs) like the Oculus Rift and HTC Vive as well as their respective handheld controllers, in addition to VR CAVEs, powerwalls, and desktop systems. The software allows engineers to create virtual simulations of devices, products, and environments and is targeted at process release engineers, manufacturing process engineers, assembly tooling program managers, and ergonomic engineers across a variety of manufacturing and assembly industries.

Using VR, engineers can explore scale models of their designs, interacting with them as they would the actual object, or they can adjust the scale for deeper inspection of specific components. Imagine, an automotive engineer being able to view a vehicle at scale in real time, but also expand the scale to get a detailed view of a specific part, like a spark plug. ESI Group’s aim is to cut costs and improve efficiency by allowing engineers to verify product designs virtually before any physical object is produced or assembled.

>> Chris Wiltz, Design News, February 22, 2017

Continuous improvement isn’t enough: Industry 4.0 sets a new bar

Industry 4.0 provides manufacturers with opportunities to transform digitally and uncover value within their operations. It leverages internet-connected technologies to improve existing processes and deploy continuous improvement activities by centralizing operational data to deliver real-time and actionable information.

Continuous improvement allows manufacturers to optimize what they already know about their operations, but Industry 4.0 creates a production environment that may uncover hidden opportunities within an existing process. It is also redefining the manufacturing supply chain by transforming manufacturers’ relationships with their customers, and their customers’ experience with end products. This will force manufacturers to realize that continuous improvement has a glass ceiling; that existing processes can plateau and eventually realize diminishing returns on investment that lead only to incremental changes.

These shifts are being accomplished through higher levels of integration and connectivity in the digital manufacturing landscape. Industry has moved from push to pull business models, where modular products are unified with post-delivery services. Industry 4.0 connects a product to its producer even after it has left the plant, creating a digital footprint that allows companies to capture data, analyze it and learn from it to continuously improve across their entire supply chain.

Despite the well-documented advantages of Industry 4.0 and the Industrial Internet of Things, manufacturers have been slow to adopt these technologies, particularly among Canadian companies. Manufacturers that are slow to adopt, risk getting lost in a world where the digitization of the global industry is accelerating risk include: limited or delayed communication within the supply chain network; or, fallbacks in technology or processes when accommodating consumer needs for product differentiation.

Industry 4.0 will disrupt companies. But those manufacturers that leverage advanced technologies across their value chains will gain significant competitive advantage to meet the changing and demanding needs of their customers.

>> Read more by Simon Drexler, Plant, February 27, 2017

How Intelligent Machines Learn to Make Sense of the World

Organizations are turning to machine learning in droves to differentiate and innovate their offerings.  You might recognize it. It is what Apple uses (along with many other online vendors) to present customers with relevant apps or products.  Gartner Fellow and Vice President Tom Austin recently noted that about half of large enterprises are experimenting with “smart computing” projects.

There are also some vendors that categorize their solutions as machine learning, whether they meet the definition or not. With all the jargon, there is bound to be confusion. Approaches like cognitive computing, come in many flavors – machine learning, natural language processing and deep learning.  And old terms, like neural networks, are coming back.

Unlike standard algorithms that are designed to perform a particular task, machine learning methods are designed to learn how to perform a task – learning as they are exposed to data. Just as humans have different learning styles, machines can learn in different ways. These learning methods include supervised learning, semi-supervised learning, unsupervised learning, and reinforcement techniques.

Machine learning lies at the heart of many advanced intelligence solutions, from AI to deep learning neural networks to natural language processing (NLP) and cognitive computing.

Today’s market is seeing an explosion in machine learning – from AI to deep learning to cognitive computing. Why now? We owe these breakthroughs to advances in inexpensive commodity hardware that can be chained together to form massively parallel computational environments. Machine learning software can now execute across hardware clusters, running learning processing in tandem- whether in-memory, in-database or both. These environments can hold all the big data necessary to feed greedy methods like deep learning. By centralizing input data, these systems give algorithms unprecedented maneuverability to cycle through neural layer iterations, test reinforcement rewards and fuse different types of data – while delivering answers at human-like speed.

>>Read more by Fiona McNeill and Dr. Hui Li, Datanami, January 31, 2017