Artificial Intelligence, always known as AI, along with its sometime companion robots leads the mainstream media hype cycle. It’s going to put everyone out of jobs, destroy civilization as we know it, and probable destroy the planet.
I lived through the Japanese robotic revolution-that-wasn’t in the 80s. Media loved stories about robots taking over and how Japan was going to rule the industrialized world because they had so many. Probing the details told an entirely different story. Japan and the US counted robots differently. What we called simple pick-and-place mechanisms they called robots.
What set Japanese industrial companies apart in those days was not technology. It was management. The Toyota Production Method (aka Lean Manufacturing) turned the manufacturing world on its head.
My take for years based on living in manufacturing and selling and installing automation has been, and still is, that much of this technology actually assisted humans—it performed the dangerous work, removing humans from danger, taking over repetitive tasks that lead to long-term stress related injuries, and performing work humans realistically couldn’t do.
Now for AI. This press release went out the other day, “With AI, humans and machines work smarter and better, together.” So, I was intrigued. How do they define AI and what does it do?
Sensai, an augmented productivity platform for manufacturing operations, recently announced the launch of its pilot program in the United States. Sensai increases throughput and decreases downtime with an AI technology that enables manufacturing operations teams to effectively monitor machinery, accurately diagnose problems before they happen and quickly implement solutions.
The company says it empowers both people and digital transformation using a cloud-based collaboration hub.
“The possibility for momentous change within manufacturing operations through digital transformation is here and now,” said Porfirio Lima, CEO of Sensai. “As an augmented productivity platform, Sensai integrates seamlessly into old or new machinery and instantly maximizes uptime and productivity by harnessing the power of real time data, analytics and predictive AI. Armed with this information, every person involved – from the shop floor to the top floor – has the power to make better and faster decisions to increase productivity. Sensai is a true digital partner for the operations and maintenance team as the manufacturing industry takes the next step in digital transformation.”
By installing a set of non-invasive wireless sensors that interconnect through a smart mesh network of gateways, Sensai collects data through its IIoT Hub, gateways and sensors, and sends it to the cloud or an on-premise location to be processed and secured. Data visualization and collaboration are fostered through user-friendly dashboards, mobile applications and cloud-based connectivity to machinery.
The AI part
Sensai’s differentiator is that it provides a full state of awareness, not only of the current status, but also of the future conditions of the people, assets and processes on the manufacturing floor. Sensai will learn a businesses’ process and systems with coaching from machine operators, process and maintenance engineers. It will then make recommendations based on repeating patterns that were not previously detected. Sensai does this by assessing the team’s experiences and historical data from the knowledge base and cross checking patterns of previous failures against a real-time feed. With this information, Sensai provides recommendations to avoid costly downtime and production shutdowns. Sensai is a true digital peer connecting variables in ways that are not humanly possible to process at the speed required on a today’s modern plant floor.
About the Pilot Program
Participation in Sensai’s pilot program is possible now for interested manufacturers. Already incorporated throughout Metalsa, a leading global manufacturer of automotive structural components, Sensai is set to digitally disrupt the manufacturing industry through AI, including those in automotive, heavy metal and stamping, construction materials, consumer goods and more.
Porfirio Lima, Sensai CEO, answered a number of follow up questions I had. (I hate when I receive press releases with lots of vague benefits and buzz words.)
1. You mention AI, What specifically is meant by AI and how is it used?
Sensai uses many different aspects of Artificial Intelligence. We are specifically focused on machine learning (ML), natural language processing (NLP), deep learning, data science, and predictive analytics. When used together correctly, these tools serve a specific use case allowing us to generate knowledge from the resulting data. We use NLP to enable human and computer interaction helping us derive meaning from human input. We use ML and deep learning to learn from data and create predictive and statistical models. Finally, we use data science and predictive analytics to extract insights from the unstructured data deriving from multiple sources. All of these tools and techniques allow us to cultivate an environment of meaningful data that is coming from people, sensors, programmable logistics controllers (PLCs) and business systems.
2. “Learn processes through operators”—How do you get the input, how do you log it, how does it feed it back?
Our primary sources of data (inputs) are people, sensors, PLCs, and business systems. In the case of people on the shop floor or operators, we created a very intuitive and easy to use interface that they can use on their cellphones or in the Human Machine Interfaces (HMIs) that are installed in their machines, so they can give us feedback about the root causes of failures and machine stoppages. We acquire this data in real-time and utilize complex machine learning algorithms to generate knowledge that people can use in their day-to-day operations. Currently, we offer web and mobile interfaces so that users can quickly consume this knowledge to make decisions. We then store their decisions in our system and correlate it with the existing data allowing us to optimize their decision-making process through time. The more a set of decisions and conditions repeats, the easier for our system is to determine the expected outcome of a given set of data.
3. Pattern? What patterns? How is it derived? Where did the data come from? How is it displayed to managers/engineers?
We create “digital fingerprints” (patterns) with ALL the data we are collecting. These “patterns” allow us to see how indicators look before a failure occurs, enabling us to then predict when another failure will happen. Data comes from the machine operators, the machines or equipment, our sensors, and other systems that have been integrated to Sensai’s IIOT hub.
We trigger alerts to let managers and engineers know that a specific situation is happening. They are then able to review it in their cellphones as a push notification that takes them to a detailed description of the condition in their web browser where they can review more information in depth.
4. What specifically are you looking for from the pilots?
We are not a cumbersome solution, for us is all about staying true about agility and value creation. We look for pilots that can give us four main outcomes:
– Learn more about our customer needs and how to better serve them
– A clear business case that can deliver ROI in less than 6 months after implementation and can begin demonstrating value in less than 3 months.
– A pilot that is easy to scale up and replicate across the organization so we can take the findings from the pilot and capitalize them in a short period of time.
– A pilot that can help Sensai and its customers create a state of suspended disbelief that technology can truly deliver the value that is intended and that can be quickly deployed across the entire organization.
My latest email from The Information highlighted the woes and tribulations of Tesla. There are headlines in all the major media outlets—manufacturing problems at Tesla impacting stock price, profitability, and cash flow.
How would you like to be the engineers who “over automated” the factory according to the boss (Elon Musk)? Want to be the Director of Manufacturing hung out to dry in the Wall Street Journal or The New York Times?
Just consider all this and see how you matter to the company—the employees, stockholders, customers.
Tesla’s 2018 is starting to look like Uber’s 2017: Every week there is a new allegation or setback about workplace culture or business performance or the quality of its products. In this case, an investigative report by Reveal says that Tesla consistently under-reported ailments suffered by workers at its main production plant. “Everything took a back seat to production,” said a former safety manager, Justine White, who left at the start of 2017. “It’s just a matter of time before somebody gets killed.” Tesla, as is its custom, fired back by calling the report by Reveal, which is part of the nonprofit Center for Investigative Reporting, a tool of an “extremist organization” that is trying to unionize Tesla’s workers and that reporters misunderstood how injuries are reviewed. We suggest reading the Reveal report and Tesla’s response, and coming to your own conclusion. (the Reveal)
And another quote from The Information about a class action lawsuit where the former director of manufacturing is giving information to the plaintiffs.
It’s not common for a shareholder class-action lawsuit, typically filed after a stock’s value has fallen precipitously, to get buzz among reporters. But this one against Tesla and its CEO Elon Musk seems unique: No fewer than 11 former workers at Tesla, including an ex-director of manufacturing at the company’s main car-production plant, provided information to the plaintiffs’ lawyers who filed the suit, according to an amended filing from March 23. It alleges Musk knowingly made false statements to investors that Tesla would be able to make 5,000 Model 3 sedans per week by the end of 2017, despite being told by his subordinates that that would never happen and continued to do so in the face of mounting evidence. Tesla’s stock dropped in price by 20% between May 2017 and November of that year, after it became clear that production target would not be met—not by a long shot. Five months later, the production pace is about 2,000 per week, Tesla has said. A spokesman for the company didn’t immediately respond to a request for comment about the suit, which is worth reading.
We have an important role within our companies. We must always consider that. Sometimes even being required to tell overoptimistic executives the reality of manufacturing.
From in-store shopper research to evaluating the gaze of an expert pianist, thousands are using wearable eye trackers to accurately measure what people see as they move freely in a range of real-world settings.
However, the design of the eye trackers has excluded certain sports and sectors from using the technology to its full potential due to the restrictions caused by protective headwear.
That is, until now. Two new versions of Tobii Pro Glasses 2 have been developed to fit easily under helmets and safety accessories, allowing athletes, industrial workers and other professionals to participate in eye tracking research. By moving the processor box below the temple the Helmet edition facilitates the use of most safety equipment while the Integration edition can be purpose fitted to most headwear thanks to it’s reduced frame and movable processor box.
Expanding the benefits of eye tracking for sports research
As sports become increasingly more competitive, athletes need to stay ahead of the game. To do so, many coaches are opting to make cutting edge technologies like eye tracking an integral part of their evaluation and training programs.
The beauty of eye tracking is that it reveals methods and techniques which occur instinctively or too quickly to be observed. Basketball, golf, and tennis are just a few of the sports utilizing wearable eye trackers to compare the visual strategies of experts and novices in a bid to identify the best techniques and fine-tune strategies.
William Rahm, a goalie coach with the Swedish Hockey League, is using eye tracking glasses to train his goalies. According to him, one of the greatest challenges as a coach is being able to understand what a player sees on the ice. Being able to watch in real-time how a goalie tracks the puck with their eyes and scans the ice during a game will help him expedite training and translate subconscious actions into, teachable strategies.
The new editions of these wearable eye trackers open up increased possibilities for this growing area of eye tracking research in sports.
Design improvements are delivering increased research opportunities across a range of sports like cricket, American football, and baseball as headgear limitations are greatly reduced or removed.
Improving safety in the workplace with eye tracking
Changes to the physical specifications of wearable eye trackers is also increasing the applications of their use to improve workplace safety. By seeing operations through the eyes of workers, management can gain greater insight into inefficient processes, distractions and unsafe conditions.
This is an important area for all. The University of Nebraska used wearable eye trackers to investigate the nature of human error on construction sites and their underlying causes. Their findings, about the importance of situational awareness, yielded a reliable model for predicting human error and preventing subsequent injuries on construction sites. This model can be used by safety managers to identify at-risk workers and prevent potentially fatal situations, which is of particular relevance to those in the sectors like mining and manufacturing.
There’s an increased scope for eye tracking research which is accompanied by other measures of human behavior. Through its recent integration with Qualisys, a provider of motion capture technology, it’s possible to access combined real-time output of both eye tracking and motion data. This provides essential information needed to further improve sports performance, diagnose visual-motor disorders, and much more.
Sometimes I wonder–Is it time for the entire Boomer generation to retire and pass the baton to the next generation? Here is another survey, this one on cybersecurity, that reveals executives know about a problem but have few or no plans to solve it soon.
People tell me constantly about surveys such as this one or training opportunities where executives and engineers in Europe pursue knowledge and those in Asia cannot satisfy their demand for standards and knowledge. And in the US? Not so much interest.
Here is a poll by a security company, Indegy, who (maybe not so surprisingly since it sells solutions) uncovered the gap yet again.
The poll found that nearly 60 percent of executives at critical infrastructure operators polled in a recent survey said they lack appropriate controls to protect their environments from security threats. As expected, nearly half of all respondents indicated their organizations plan to increase spending for industrial control system (ICS) security measures in the next 12-24 months.
“We have been tracking the escalation in cyber threat activity specifically targeting critical infrastructures for some time,” says Barak Perelman, CEO of Indegy. “As the recent joint DHS/FBI CERT Technical Alert illustrates, adversaries have compromised facilities across the US to conduct reconnaissance and likely develop “Red Button” capability for future attacks.”
Lack of Visibility and Control Cited
While organizations have made significant investments to secure their IT infrastructures, they have not fully addressed threats to operational technology (OT) environments. The recent Indegy poll of nearly 100 executives from various critical infrastructure organizations underscores the lack of preparedness in key sectors including energy, utilities and manufacturing. Among the key findings:
35% of respondents said they have little visibility into the current state of security within their environment, while 23% reported they have no visibility
63% claimed that insider threats and misconfigurations are the biggest security risks they currently face
57% said they are not confident that their organization, and other infrastructure companies, are in control of OT security
Meanwhile, 44% of respondents indicated an increase in ICS spending was planned in the next 12 to 24 months, with 29% reporting they were not sure
Some people have told me that they prefer the YouTube versions of my podcasts. Not sure why. Here is the latest one. 173-Digital Twins and the Internet of Things. Discussing trips to San Diego and the Industry of Things World event (Internet of Things, Mindsphere from Siemens, OPC UA) and Siemens Manufacturing in America (university students, simulation, PLM, digitalization, cyber-physical systems, blockchain).
You can subscribe to the podcast version on Podcasts (iTunes) or on Overcast or wherever you find podcasts. Or click the podcast button on this website. Or click here.
One of the many dreams spurring development of the Industrial IoT was the ability to easily slap sensors around a plant on units and equipment and areas that would report to a database with attached dashboards. The resulting information and visualization would give plant managers and professionals an opportunity for better control of operations and maintenance. Following is a press release from a relatively new entrant in that market segment.
This system from Swift Sensors reminds me of the old ZigBee sensors from a long time ago brought into the modern IoT world with new technologies. This month, the company announced addition of user-defined dashboards to simplify and enhance viewing and analytics of critical sensor data. These new features will help Swift Sensors customers gain deeper insight into “big data” from wireless sensor networks and simplify IoT systems to deliver true value.
“Providing a simple, intuitive cloud dashboard is essential to driving value from a wireless sensor (IoT) system,” says Sam Cece, founder and CEO of Swift Sensors. “Our end-to-end system delivers simplicity and value at all levels — from installation to configuration to data analytics.”
The Swift Sensors cloud-based dashboard allows real-time asset monitoring and sophisticated analytics from anywhere. The enhanced dashboard will allow customers to show sensor data in the manner that’s most relevant to their business, including the option to create multiple views of data streams to identify patterns and correlations.
More details on the new dashboard features:
Custom Dashboards: Users can now create custom dashboards shared with all account users. Custom Dashboards are user-defined pages with a collection of panels with only the data users want to see, in the order they want to see it. Customer Use: Aerospace manufacturing company uses custom dashboard to track sensors measuring machine output and utilization.
Set Default Dashboard: Users can select their favorite dashboard to be their default view. When a Dashboard is marked as the default view, the user will be taken directly to this Dashboard upon signing into Swift Sensors.
Customer Use: A 1000 seat restaurant and banquet facility manager creates default view for walk-in coolers and freezers.
Combo Chart: The dashboard now supports a new Combo Chart panel. This panel allows up to four measurements to be rendered on the same chart, even if those measurements use different units.
Customer Use: A large food manufacturer tracks vibration and temperature data to enhance preventive maintenance program.
Expanded Language Support: Support for six new languages has been added. In addition to English and Japanese, users can now also choose Danish, German, Spanish, French, Italian, and Portuguese.
Full Screen App behavior on mobile devices: The Swift Sensors Dashboard behaves like a full-screen app on mobile devices, thanks to full-screen support when launched from a Home Screen icon on iOS and Android.
Incomplete Threshold and Notification Warning: Threshold and notification lists now show a yellow warning icon next to incomplete thresholds and notifications with missing assignments of users, measurements, bridges, and/or sensors
Swift Sensors products are available through a worldwide network of resellers and integrators. All features of the Dashboard are available to Swift Sensors customers through a low annual subscription to the Cloud Dashboard and Analytics, with configurations optimized for the size of the facility.