by Gary Mintchell | Apr 5, 2024 | Enterprise IT, Manufacturing IT, Operations Management, Software
The beginnings of a trend in manufacturing software has appeared on my horizon about mid-way through last year. This would be the use of low-code software for application development. I first noted it with some acquisitions in my market space. Recently I have begun working with a company called Quickbase who has a platform built with low-code application development in mind.
[Note: In my work with Quickbase, I’m sometimes compensated for what I do. They do not dictate what I write or say.]
I recently had the opportunity to talk with two users of Quickbase’s platform for their manufacturing software needs. You can hear them plus me at the Quickbase Empower Virtual Customer Conference on May 8 (our session is at 11:30 am EDT immediately following the keynotes). Their stories verified what I was beginning to hear from my first encounters. Listening to their tone of voice, what really perked them up was the ability to be rapidly responsive to requests from users for modifications to screens and reports.
That discussion spurred me on to some additional research on the topic. Following is a list of benefits I uncovered on my research. This is not a list specific to Quickbase, but a more generic list that you might find with applications in a variety of areas. But check out Quickbase for your specific needs. I’m sure I’ll have more interviews in the future to take a deeper dive into Quickbase specifically. For now, I was interested in this new feature. Feel free to contact me with additional thoughts. Or stories about how you have used low-code in engineering or manufacturing operations software.
- Faster Development: Low-code platforms enable rapid application development by providing pre-built templates, drag-and-drop interfaces, and visual development tools.
- Reduced Costs: With low-code development, you can save on development costs by eliminating the need for hiring expensive developers with specialized coding skills. Additionally, the time saved in development translates to cost savings.
- Increased Productivity: Low-code platforms allow both professional developers and citizen developers (non-technical users) to build applications. This democratization of app development increases productivity by enabling more people within an organization to contribute to development efforts.
- Flexibility and Customization: While low-code platforms provide pre-built components and templates, they also offer the flexibility to customize applications according to specific business requirements. Developers can extend functionality by writing custom code when needed.
- Streamlined Maintenance: Low-code platforms often include built-in features for application monitoring, debugging, and performance optimization. This simplifies maintenance tasks and reduces the time required for ongoing support and updates.
- Integration Capabilities: Many low-code platforms offer out-of-the-box integrations with popular third-party services, databases, and APIs. This makes it easier to connect your applications with other systems and data sources.
- Scalability: Low-code platforms can scale with your business needs, allowing you to quickly add new features or expand functionality as your requirements evolve. This scalability helps future-proof your applications.
- Accessibility: Low-code platforms often come with intuitive user interfaces and guided development processes, making app development accessible to a wider range of users, including those with limited technical expertise.
- Faster Time-to-Market: By accelerating the development process and enabling iterative development cycles, low-code platforms help bring applications to market faster. This can give your business a competitive edge by allowing you to respond quickly to changing market demands.
- Risk Reduction: Low-code platforms often come with built-in security features and compliance standards, reducing the risk of security vulnerabilities and ensuring regulatory compliance.
Overall, low-code application development software offers a compelling solution for businesses looking to rapidly build, deploy, and maintain applications with greater efficiency and flexibility.
by Gary Mintchell | Apr 3, 2024 | Automation, Robots, Software, Technology
Vision software for guiding robots news goes along with the burst of robot news. In this case, AI meets vision software.
AI software company Micropsi Industries today announced MIRAI 2, the latest generation of its AI-vision software for robotic automation. MIRAI 2 comes with five new features that enhance manufacturers’ ability to reliably solve automation tasks with variance in position, shape, color, lighting or background.
What sets the MIRAI 2 AI-Vision Software apart from traditional vision solutions is the ability to operate with real factory data without the need for CAD data, controlled light, visual-feature predefinition or extensive knowledge of computer vision.
Gary Jackson, CEO of Micropsi Industries, noted, “Recognizing the complexities of implementing advanced AI in robotic systems, we’ve assembled expert teams that combine our in-house talent with select system integration partners to ensure that our customers’ projects are supported successfully, no matter how complex the requirements.”
MIRAI is an advanced AI-vision software system that enables robots to dynamically respond to varying conditions within their factory environment, including variance in position, shape, color, lighting and background. What sets MIRAI apart from traditional vision solutions is the ability to operate with real factory data without the need for CAD data, controlled light, visual-feature predefinition or extensive knowledge of computer vision.
The five new features that will be available to MIRAI 2 users are:
Robot skill-sharing: This new feature allows users to share skills between multiple robots, at the same site or elsewhere. If conditions are identical (lighting, background, etc.), very little or no additional training is required in additional installations. MIRAI can also handle small differences in conditions by recording data from multiple installations into a single, robust skill.
Semi-automatic data recording: Semi-automatic training allows users to record episodes (of data) for skills without having to hand-guide the robot, reducing the workload on users and increasing the quality of the recorded data. MIRAI can now automatically record all the relevant data—users only need to prepare the training situations and corresponding robot target poses.
No F/T sensor: Training and running skills is now possible without ever connecting a Force/Torque sensor. This reduces cost, simplifies tool geometry and cabling setup, and overall makes skill applications more robust and easier to train.
Abnormal condition detection: MIRAI can now be configured to stop skills when unexpected conditions are encountered, allowing users to handle these exceptions in their robot program or alert a human operator.
Industrial PC: The MIRAI software can now be run on a selection of industrial-grade hardware for higher dependability in rough factory conditions.
by Gary Mintchell | Apr 2, 2024 | Automation, Process Control, Productivity, Software, Sustainability
Fero Labs has developed software to help certain types of process manufacturing plants improve quality output economically when given a random mix of feedstock. I wrote about the company last August—A Better Way to Control Process Quality.
They sent a new press release, and I must admit that I understood almost nothing in it:
Fero Labs, the only Profitable Sustainability Platform for industrial optimization, announced the release of their ground-breaking feature ‘ExplainIt for Live Predictions’ which expands a factory’s production knowledge in real-time. This advanced feature for cross-functional teams increases trust in AI predictions by disclosing real-time text explanations about abnormal factors influencing their live production.
There were way too many marketing-type phrases in there. Worst of all was the concept of “trust in AI predictions.” So, I asked the very patient publicist. She suggested that I talk with Berk Birand, Fero Labs Co-founder and CEO. And, I did. He was most helpful.
We caught up from my last article about their ability to use the huge data sets manufacturers have accumulated over the past decade using advanced statistical methods and “white box machine learning (ML)” to help engineers optimize their plants. Make them more profitable and reduce waste (sustainability). Therefore the “Profitable Sustainability” company.
Birand took me through an example that I could understand, since I had a customer in the 90s who did this sort of process.
Imagine a plant with piles of scrap steel in a yard. They have an electric arc furnace that melts all that disparate steel that will be poured out eventually to make their final product. Given that the feedstock has high variability as to the composition of the steel, the typical plant overdesigns the process to allow for variations. This, of course, is wasteful on the surface. But if the final chemical analysis shows that the output will not make the desired tensile strength or other spec, then the waste is even higher.
What if you accumulated the data (feedstock, process, finished steel) over time built a modern AI model? Its predictions could be used to drive profits, reduce waste, save time. But, would anyone trust yet another advanced process control system? We all know that models eventually goes out of whack sometimes and sometimes gets the wrong answer.
Here comes the “trust” part of the trust in AI model. They built an explainable model from the beginning. It can predict characteristics, say tensile strength of the mix because of chromium or carbon levels and so forth. Since we know that every model is wrong sometimes, they built in confidence levels in the prediction engine. Their AI looks at the material composition and suggests adding chemicals to the mix, but it gives an explanation and a confidence level. The engineer looks at the confidence report (I am confident in this prediction or I’m not confident in this prediction) and can decide whether to go with the AI or to go with gut feel based on years of experience.
He convinced me. Fero Labs has developed an AI engine that gives the engineer a level of trust in the prediction.
More explanation from the press release:
Expanding on Fero Labs’ white-box ML, which provides full transparency of Fero’s powerful machine learning models, the new ExplainIt feature provides a contextual explanation of anomalous factors involved in each live production optimization.
This type of analysis is typically addressed through linear Root Cause Analysis (RCA) tools. Unlike traditional methods, Fero Labs’ solution is non-linear, much like process operations, and delivers results in seconds rather than the hours or days typically needed. Traditional methods generally require the engineer to preselect a small sample of factors to investigate, which can introduce potentially misleading biases. Fero Labs’ software has the power to evaluate all relevant factors which improves insight and prediction accuracy.
by Gary Mintchell | Mar 27, 2024 | Automation, Industrial Computers, Operator Interface, Technology, Workforce
Still more catching up on news from the recent MODEX trade show in Atlanta. Zebra Technologies has grown from a specialty printer company that I used for a couple of projects in the 90s to an interesting automation solutions company. It has introduced extensions to its wide range of mobile compute and connectivity devices. This news details a number of new products designed to enable quality work from your front-line workers.
First a note about some research the company conducted. None of these findings shock me.
Operations leaders in the manufacturing, warehouse, retail, and transportation and logistics industries worldwide continue to grapple with fostering resilient supply chains amid heightened omnichannel demands for speed and accuracy, ongoing labor shortages, and economic uncertainty. Recognizing the criticality of an optimized supply chain, 89% of decision-makers surveyed in Zebra’s 2023 Global Warehouse Study say if their organizations do not invest in technology to improve operations, they will not meet their business objectives.
According to Zebra’s study, eight in 10 decision-makers and frontline workers said using more technology and automation would help meet or exceed productivity goals. In addition, decision-makers (54%) and workers (49%) agree addressing worker comfort and ergonomics is a top workforce initiative.
And something about a number of new products.
Zebra’s new RS2100 wearable scanner – the industry’s smallest back-of-hand (BOH) scanner – enhances productivity and delivers new levels of comfort to workers. The unique mount on the RS2100 leaves the palm completely unobstructed, providing greater freedom to handle items.
Zebra will also launch the WT6400 and WT5400 wearable computers. Engineered to streamline hands-free workflows while enhancing comfort, the WT6400 and WT5400 provide more flexibility for picking orders, sorting items, and managing inventory with greater efficiency and accuracy. With a larger display and integrated keyboard, the WT6400 is easily accessible for right- and left-handed workers, and its integrated angled camera captures images to document damaged items or completed tasks. The WT6400 is designed for demanding environments, including freezer operation (-30°C), while the WT5400 introduces a new class of wearable computers for hands-free retail workflows.
A new addition to Zebra’s TC5X series are the TC53e/TC58e/TC53e-RFID mobile computers. Designed to meet today’s latest standards, the TC5Xe series offers 5G, Wi-Fi 6E, integrated RFID, premium security features and contains 25% post-consumer recycled plastic by mass. The TC53e-RFID offers integrated short-range UHF RFID, enabling associates to take inventory in the backroom, validate tickets at a concert or verify all items in a shopping cart from up to nearly 4 ft/1.2m away with the same device ergonomics as the standard TC53e.
The TC5Xe series, WT6400 and WT5400 are all powered by the Qualcomm QCM4490 processor and Qualcomm QCS4490 processor which provide long lifecycles and more processing power compared to previous generations. These devices can run multiple applications including apps powered by augmented reality and AI, apps designed for voice and line of business as well as simple ‘green screen’ legacy apps.
Beyond its new wearables and mobile computers, Zebra will also showcase its recently launched MC9400 series, the ultra-rugged mobile computer designed to enhance workflow efficiency and device security across the retail, warehouse, manufacturing, and transportation and logistics industries.
by Gary Mintchell | Mar 26, 2024 | Automation, Edge, Internet of Things, Open Source, Operations Management
The 5th annual Eclipse Foundation IoT and Edge Commercial Adoption Survey actually holds few surprise but shows ongoing trends of investment. I’m not sure if it is good news or worrisome that the C-suite seems to be more involved. These people hold the purse strings, but they also usually hold unrealistic expectations (oversold by engineers?) about the eventual benefits of technology adoption.
The survey includes a comprehensive analysis derived from responses of over 1067 professionals in the IoT and edge computing domain. Conducted online from April 4 to July 5, 2023, the survey offers valuable insights into the evolving IoT and edge computing ecosystems by identifying the requirements, priorities, and challenges faced by organisations that deploy and use commercial solutions, including those based on open source technologies.
“Consistent with our previous surveys, the continuous growth and adoption of IoT and edge computing remains evident. The data reflects a notable increase in the number of managed devices and larger investments, indicative of a scale-up in deployments,” said Mike Milinkovich, executive director of the Eclipse Foundation. “Particularly notable is that the C-suite significantly influences decision-making for IoT and edge investments. This underscores the strategic value that businesses place on solutions based on open technologies in real-world deployments. Open source components are recognised as vital enablers of success.”
Six of the key takeaways from the survey data include:
- IoT Adoption Surged in 2023: 64% of respondents are now deploying IoT solutions, up from 53% in 2022. An additional 23% plan to deploy within 12-24 months. Less than 5% have no IoT deployment plan.
- Edge Computing Adoption Holds Steady, Acceleration Anticipated: Adoption of edge computing solutions remains at 33% (same as 2022), with an additional 30% indicating plans to deploy within the next 24 months. 27% are still evaluating edge platforms, while only 10% have no plans to deploy edge solutions.
- Rising Investments Signal Scale-Up in Production Deployments: 17% of respondents spent between $1-10M in 2023 (more than double that of 2022), growing to 23% in 2024. 5% anticipate spending over $10M. This trend indicates a transition from proof-of-concept to ROI-focused deployments.
- Growing Number of IoT & Edge Assets per Deployment: Deployments of fewer than 1K managed assets will remain steady or decline, while larger deployments are on the rise, with an impressive 10% of deployments consisting of 50K or more devices. Regarding asset implementation, the mix between greenfield and brownfield is almost equal.
- IoT is Increasingly Strategic with the C-Suite Driving Investment Decisions: 49% of organisations reveal that the C-suite predominantly drives decisions. This marks a significant increase from the 38% reported in 2022, indicating a growing influence of top-level executives in shaping investment choices within the realm of IoT and edge technologies.
- 75% of Organisations Surveyed Embrace Open Source in IoT and Edge: 75% of organisations are actively incorporating open source into their deployment plans. The widespread use of IoT and edge solutions based on open source technologies highlights how open source has become key in shaping today’s technology landscape.
The IoT and Edge Commercial Adoption Survey is sponsored by the Eclipse IoT and Sparkplug Working Groups. It serves as a valuable complement to the annual IoT Developer Survey, a vital source of strategic insights from the development front lines. The Eclipse IoT community represents one of the largest IoT-focused open source collaborations in the world, with 45 members and over 50 projects. Eclipse IoT projects have been broadly adopted by leading organisations across a variety of verticals to deliver commercial IoT and edge-based solutions and services.
by Gary Mintchell | Mar 25, 2024 | Software, Technology
Kevin Rose interviews Chris Dixon recently. Dixon provides a good overview of the current status of blockchain. I really haven’t heard much about that technology for years. A speaker at a Siemens event maybe five years ago extolled the future of pharmaceutical supply chain data through blockchain. That may have been the last I heard. Check out the podcast for an update.
Meanwhile, according to research from Global Data, “The blockchain industry, although volatile and nascent, has made significant progress in a short span of time, driven by remarkable innovation. Global blockchain platform and services revenue is set to grow from $12 billion in 2023 to $291 billion in 2030. This growth trajectory reflects a more delineated and specialized expenditure pattern, with specific areas such as asset tokenization, blockchain development, and infrastructure services serving as primary drivers of market expansion.”
GlobalData’s latest report, “Thematic Research: Blockchain,” reveals a pivotal shift from the technology’s broad, indiscriminate application to more focused, strategic uses. The industry is witnessing a quiet but steady increase in blockchain adoption, concentrating on its practical benefits. This trend is supported by a growing understanding that blockchain’s applicability is not universal and that a robust digital infrastructure is crucial for its successful deployment.
