Areas of Innovation in Smart Manufacturing
Leading the first mHUB Accelerated Incubation cohort, I have the pleasure to talk to hundreds of startups. Hardtech startups that are breeding new solutions to challenges in manufacturing. Startups that create novel products, services and business models to make manufacturing smarter. Anywhere between sketches on a napkin, to solid prototypes to deployed pilot projects at client locations.
Fascinating stuff if you ask me! Here are some focal areas, by no means complete, rather an impression of evolutions that stood out. And, a link to the startups in our IIoT cohort.
Continued improvement of productivity and efficiency
There is a plethora of sensors for an ever-expanding application field — from manufacturing and warehousing to agriculture, construction and more. Still, there is a lot of opportunity for dedicated sensors with new applications and new business models: think about air quality sensing (in plants, and even in city neighborhoods for citizen wellbeing); flow sensing devices based on vibration technology (rather than in-traffic sensors); visual sensors making shelves smart for better inventory management; quality assurance sensors providing real-time production process feedback. In the same vein combinations of sensors in more robust and smart devices are gaining traction in specific markets too: e.g. combo sensors in agriculture for food growth optimization.
The wellbeing of machine operators
With Covid19, startups have been focused on wearables and platforms that adhere workers to strict social distancing measures, or smart devices geared towards enforcing hygiene rules.
Startups, however, are also envisioning the long-term evolutions of wearables and platforms for a broader support of the safety and wellbeing of workers.
E.g. ensuring safety of co-workers by tracking their position versus machines or identifying worker fatigue, by providing operators environment awareness and communication capability in hazardous environments. The step from safety to wellbeing is on the horizon: e.g. wearable ear devices that allow workers to set their own soundtrack (do you also work better while listening to your preferred music?) but still have full attention to critical contextual signals (machines, robots, commands).
Improving the worker experience
Lots of work has gone into improving the worker experience but so far it has mostly driven by an inherent focus on increasing worker productivity. Think about the field engineer who is in direct voice and video connection with the home base to get real-time guidance. Innovation is ongoing to further improve the quality and make such solutions cost effective.
The whole space of remote workers requiring instrumentation and toolsets is being revisited resulting in connected miniaturized versions that fit in your pocket —
think of shrinking bulky desktop lab instruments in the same way as big old desktop computers now fit in the palm of your hand. But also within factories and warehouses, initial versions of exoskeletons have been introduced to aid operators and workers. Work is now already happening on sensors that will help these workers to control their exoskeletons for improve wellbeing and safety.
Finetuning the automated co-worker (aka the robot)
Tremendous innovation is taking place in the broader robotics field. Smarter robots that sense the presence of a human making the plant a safer place for operators, and smarter autonomous vehicles in warehouses and manufacturing campuses that are integrated in inventory management systems. Remotely human-operated robots working in potentially harmful environments, and improved robot capabilities through flexible joints for additional maneuverability and handling capability. In sum, cost-effective robots that can easily be configured and installed in various environments with a not so far-out vision of self-configuring and self-learning.
Focus on energy efficiency towards sustainability
A major challenge in the sensor and edge device market has been the need for power to keep devices humming. Often sensors are battery powered that last several years. However, more and more devices that combine sensing, location and computing need higher and permanent energy sources resulting in three paths of innovation. Energy harvesting innovation based on vibration technology or the use of nano-capabilities of certain materials; typical power-hungry location tracking devices are being replaced by low-power versions ideal for asset tracking purposes; and sensors developed towards designing more sustainable solutions covering most of the value chain .
Ongoing interoperability and security
Interoperability between sensors, edge devices and the cloud has always been an important challenge in order to allow smooth transmission of sensor data to computing platforms for analytics. Uniform standards are lacking but work on this front is happening. Whereas 5G is full of promises in the long-term, low power long range wide area networks (LoRaWAN) that don’t require massive infrastructure are en vogue now.
Even more important is having a secure communication between all components of the end-to-end IoT system.
Preventing hacking to avoid compromising manufacturing-critical data that could stop a plant’s operation or stealing that data for competitive purposes is getting higher on the industry 4.0 agenda. A difficult balancing act, however, between sufficient processing power accelerating computation / encryption and the amount of energy to power these devices. A lot of innovation is happening at the software, system and hardtech level by startups. More so than by established players who prefer to keep their solutions under their own umbrella in a walled garden.
Finding the right data
Transmitting data from assets to the analytics platform is only a part of the challenge, the bigger problem is selecting the right data at the right time and the right place. Shipping all data is impossible and cost prohibitive hence the focus on more dedicated and smarter sensing devices that only transmit the relevant data. Additionally, intermediate edge devices are introduced that collect that relevant data, pre-process it and transmit only the relevant parts to the analytics platform in the cloud. In some cases, there are real-time constraints that prohibit shipping the data to the cloud and rely on more local (read edge) processing and decision making. A lot of innovation is taking place in that foggy edge environment to find the right balance between processing, transmission and decision making.
Focus on small and medium manufacturers
Consultants and integrators have been focusing on IIoT and smart manufacturing implementations in large corporations. Typically, these projects are major and expensive undertakings requiring an army of skilled professionals, more sophisticated IIoT components and platforms that are commensurate with their clients.
That leaves small and medium manufacturers in the cold as they don’t have the resources (both talent and financial) to absorb such IIoT projects.
This opens prospects for startups focusing on connected plug-and-play sensors, simple edge devices and platforms that can be easily deployed and generate meaningful insights. Such innovations can create an attractive and low-cost path for small and medium manufacturers towards digitalization.
Towards a new manufacturing model
The ongoing trend towards personalization of products results in overall lower production volume sizes (batches) that have made many rethink the whole manufacturing concept. Traditional manufacturing has always been focused on large batch sizes defining production and assembly lines. Different additive and subtractive manufacturing technologies are being contemplated for lower volume production. As a result, software is now available to guide developers as to which manufacturing technology is better suited for different product-volume combinations based on the product CAD file. Next evolutions integrate the design and the actual making of the product. We are moving to a world where high volume assembly lines are complemented (or replaced) by highly flexible manufacturing units that use the appropriate manufacturing technology — think of a super-machine that combines the flexibility of CNC machining and 3D printing all-in-one cost-effective equipment. That is flexibility.
Thanks to the startups for the inspirational talks!
Thierry Van Landegem is Executive Director of the IIoT Accelerator at mHUB, www.mhubchicago.com, the hardtech innovation center based in Chicago.
