by Gary Mintchell | May 8, 2026 | Generative AI, Manufacturing IT, Operations Management
I wrote Monday about the key role of the involvement of the frontline worker implementing new technologies such as AI. Digital transformation does not truly occur until the work is done by the frontline workers and their immediate supervisors.
This follow up post results from a survey by PwC and the Manufacturing Institute and the subsequent report From skepticism to integration: Frontline leadership in manufacturing AI adoption.
Top Findings:
- 62% of frontline workers are skeptical of AI and only 24% describe themselves as being excited about its potential and benefits
- Frontline leaders cite insufficient training (40%) and lack of clarity around the purpose of AI (38%) as the most common reasons for resistance among workers, higher than fears of job displacement (25%)
- 72% of manufacturing leaders cite resistance from employees who are comfortable with existing systems as a barrier to AI adoption, and 57% identify lack of training and readiness
- 58% of respondents reported that AI use among executive leadership remains limited; however, 74% identify leadership as the defining factor in the success of major initiatives
- 48% of manufacturing executives rate their frontline leaders as “very” or “extremely” effective in shaping to the overall employee experience of frontline workers
I talked with author Ryan Hawk about the findings. He says sometimes the organization implements an incremental bite of the apple without an overall plan. This leaves the frontline wondering what’s really going on. The keys he talked about sounds like a typical lack of leadership by management from the top down. In order to build the trust of the frontline worker, the goals and applications need to be clear from the beginning.
He responded to questions about real applications of AI, he pointed to things that have great benefit to the worker and their output. Inspection helps workers assure work quality. Predictive maintenance helps them know when to ask for technician support prior to breakdown. Sometimes the schedule or line must be rebalanced perhaps due to absenteeism or inventory. All these assist decision making, performance, and work quality.
These thoughts brought memories of the business novel The Goal by Eliyahu Goldratt. This was a story about a plant manager working to save his plant through the tool of studying constraints in the system. Innovative leaders can use these new LLMs and other AI tools to more effectively find these constraints and other problems that a good kaizen team can tackle.
“AI adoption isn’t just a technology initiative; it’s a business initiative that has the power to transform the way people work,” said PwC US Energy & Industrials Leader Ryan Hawk. “The organizations that pull ahead will be the ones that find ways to be tech-driven and people-enabled, using AI to empower their employees to solve the biggest customer and business issues. Companies that find ways to continually evolve their ways of working will see AI help unlock tangible value, efficiency and effectiveness.”
by Gary Mintchell | May 1, 2026 | Cloud, Generative AI, Manufacturing IT, Software
Yes, I know that a couple of weeks have passed since I returned from Miami and the Aras Community Event. I got a quick podcast (also YouTube) recap posted, then went on vacation. This week had more appointments than my usual month. I’ve done a bunch of research (thanks Claude) and have much to digest. That’ll be tomorrow’s work (in between helping replace my daughter’s front door hardware and catching an English Premier League game). Tonight, a concert at Chicago Symphony Center celebrating Chicago’s contributions to jazz.
I also have two things in queue regarding frontline workers–one from ACE and another a report from PwC where I finally was able to connect with the report’s author.
Finally in queue, are thoughts from the Siemens press conference from Hannover Fair. A bit of compare and contrast with the ACE experience with AI, LLMs, and agents.
Have a good weekend. Back Monday.
by Gary Mintchell | Apr 28, 2026 | Manufacturing IT, Software
Ignition 8.3.5 is here, and Inductive Automation’s Jennifer Faylor explains on the company blog.
Expanded OPC UA support
Ignition 8.3.5 delivers OPC UA support for using a Global Discovery Server, a new file-based Secret Provider type, and major improvements for large-scale systems (including an OverridesOnly tag parameter and 4X increased throughput for managed tag providers).
In Ignition 8.3.5, you now have the ability to automate the certificate management of multiple OPC servers and devices from a single Global Discovery Server (GDS). This is possible thanks to a new property on the OPC UA Server Settings page: “GDS Push Enabled.” When this new property is enabled, the server’s certificate and trust list can be managed by an external GDS.
With this new functionality you can use an external GDS to centrally manage a dispersed system. By opening the door to central certificate management with a GDS, this new feature helps strengthen security in your industrial control systems.
File-Based Secret Provider
Another security improvement in 8.3.5 is a brand new way to store secrets from your Ignition Gateway. A new “File” Secret Provider type lets you read secrets in files on disk, as opposed to storing them internally on the Gateway installation directory. This Secret Provider supports encrypted (Ignition) secrets as well as cleartext secrets.
OverridesOnly Tag Parameter
As a result of some Ignition users’ more complex scripting needs, we’ve added a new overridesOnly parameter to the system.tag.getConfiguration() function. What this means is that when you’re calling the getConfiguration function for a specific tag path, you can now have just the local (overridden) properties returned. If this new parameter is set to “True” then only overridden properties from UDT members (instances and definitions) will be returned. And if the tag is not a UDT member, then there will be no effect.
Improved Gateway Configuration
In 8.3.5, we’ve improved the performance of the Gateway’s configuration file system and added new Gateway diagnostic resource metrics.
By allowing operations on different resource types to proceed concurrently with minimal locking on changes, we’ve greatly boosted the performance and responsiveness of the Gateway’s configuration system. This update optimizes tag value handling and increases throughput by 4X for managed tag providers.
The process of writing Ignition resources (such as EAM agents, OPC UA server profiles, database connections, SIP notification profiles, and more) into the Gateway file system is now significantly improved. And thanks to the new diagnostic resource metrics, you can use the Metrics Dashboard to observe those various resources more closely.
This update is an especially big deal for anyone using MQTT modules with Ignition, since it represents a substantial increase in capabilities for customers with large systems.
Docker Utility
We added the jq command-line utility to Ignition’s Docker image for easier JSON parsing. This is a helpful addition if you’re customizing Helm charts or entrypoint scripts, since you can use this utility to grab specific properties from particular files.
Event Streams Improvements
Ignition 8.3.5 adds tooltips to each stage of an Event Stream’s data to provide you with additional context. These tooltips display upon hovering over element subtext, and update dynamically as real-time values change.
And there’s more to discover on their website.
by Gary Mintchell | Apr 27, 2026 | Manufacturing IT, Software
I had an opportunity to talk with long-time business colleague Juliann Grant at the recent Aras Community Event in Miami. She is Marketing VP at digital engineering firm Razorleaf. She’s been a great source of PLM market insight. She told me about a podcast she hosts. Stay Sharp in Digital Engineering presented by Razorleaf, is a brisk conversational look at news and technology in the space. The linked episode will improve your understanding of AI agents with Razorleaf and Diego Tamburini of CIMData.
I highly recommend both this episode and the series. You can subscribe on your favorite podcast source or on YouTube.
by Gary Mintchell | Apr 21, 2026 | Data Management, Generative AI, Manufacturing IT, Podcast, Software
I’ve posted a podcast to both my podcast channel (subscribe on any podcast app) and my YouTube channel.
A first summary of my three days with the Aras community in Miami. These PLM events always return me to the time when I did this sort of work–manually. Then my first taste of computers digitizing the bill of materials as a first step in our data management journey. Unfortunately, that company hit a big bump in the road and I was invited to try other things–at other companies.
Aras product managers showed how LLMs trained on the data within the app along with proper governance worked with agents to perform a number of tasks. Tasks in many cases that would require days of pain-staking work from a human.
While I heard from an analyst in the market that they thought this was all painfully slow, I’d offer the thought that a company does not want to outpace its customers. Most will not want to jump into the deep end immediately.
As always, this podcast was sponsored by Ignition from Inductive Automation.
by Gary Mintchell | Apr 15, 2026 | Edge, Generative AI, Manufacturing IT
It had to happen. An industrial-strength data center designed for the industrial edge. From Siemens, of course. They’re unveiling at Hannover next week. I will unfortunately not be in Hannover next week. I need funding to cover the expense, and all my past contacts have gone in other directions. Always a valuable experience.
More on the announcement:
- Siemens is making its Industrial Automation DataCenter AI-ready for powerful AI applications in production environments
- Siemens integrates accelerated AI computing power and advanced AI-specific cybersecurity from NVIDIA and Palo Alto Networks
- Single source – ready-to-operate, pre-configured and system-tested IT/OT platform for the production environment
In partnership with NVIDIA and in collaboration with Palo Alto Networks, Siemens delivers secure NVIDIA computing infrastructure at the edge for powerful AI acceleration, alongside NVIDIA BlueField data processing units (DPUs) for intelligent real-time data processing and security from Palo Alto Networks Prisma AIRS.
Delivered fully pre-installed, pre-configured, and system-tested from a single source, the turnkey solution combines high-performance virtualization for OT applications, backup and restore capabilities, data archiving, and an industrial demilitarized zone, effectively separating IT networks from OT environments. Through a strategic partnership with NVIDIA and collaboration with Palo Alto Networks, accelerated AI computing power and advanced AI-specific cybersecurity from NVIDIA and Palo Alto Networks is now enabled directly at the edge.
This evolution addresses a critical industry need: implementing standardized, pre-integrated AI infrastructure poses significant challenges for many industrial companies. Building complex, high-performance, and secure AI-capable environments is very demanding, time-consuming, and costly – with integration, installation, and system engineering alone requiring up to 80 hours. Additional risks include compatibility issues and potential operational downtime. With the enhanced Siemens Industrial Automation DataCenter, customers benefit from real-time insights, optimized processes, and enhanced efficiency, yielding substantial gains in productivity and innovation.
Siemens’ Remote Industrial Operations Services include continuous remote monitoring of IT/OT infrastructure, comprehensive cybersecurity measures, regular maintenance and preventive steps, as well as rapid support in the event of incidents. Siemens’ experts monitor and protect companies’ production environments around the clock from the Siemens OT Security Operations Center (SOC), which also reliably protects Siemens’ own facilities worldwide from cyber threats.
Remote Industrial Operations Services offer extends over the entire lifecycle of the Industrial Automation DataCenter and is also flexibly applicable to various IT systems and components in OT environments, including third-party components.
