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 4, 2026 | Operations Management, Software, Workforce
Digital transformation initiatives are all the rage—at least in the marketing release system. I remain amazed that after all the released products and articles I’ve written the software layer of PLM and MES remain under utilized. One recent concern discussed in two recent interviews focuses on frontline workers and their supervisors.
The same situation exists that I confronted 50 years ago in an early role as data manager for a manufacturing company—no appropriate work is accomplished without reliable, easily assimilate-able, and clear instructions make it to the people doing the work.
In the standard words of reporting, I caught up with Garth Coleman, CEO of Canvas Envision, at the recent Aras Community Event in Miami, FL. The was the first of my two conversations on the topic.
He told me that while over the last few years, many industries have become dynamic, data-rich, and modernized, factory floor instructions are still largely outdated with PDFs, screenshots, and text-heavy documents that are now increasingly stale.
Just as part of my job years ago, manufacturers are still struggling to align as-built with as-designed.
He argues the shift here demands interactive, model-based instructions where teams adopt systems in real-time, creating a continuous loop for operations, rather than the other way around.
Canvas Envision features these cutting-edge technologies:
- No-Code Workflows: Allowing users to build and modify instructions without the need for IT involvement.
- CAD Fidelity: Ensuring that instructions are always up-to-date with design changes through native CAD visualization.
- AI Assistance: Automating the generation of complex views and lists with Evie, the integrated AI assistant.
- Gadgets: Providing ready-to-use components like checklists and data capture.
- Integration and Flexibility: Seamlessly connecting with enterprise systems (PLM, MES) and offering flexible deployment options (SaaS or self-hosted).
Until you close that final loop aligning as-built with as-designed in a 360-degree loop, everything is only data.
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 30, 2026 | Security
The typical cybersecurity firm releases reports. Here is one from a company called Resiliance. The unique take on this concerns linking cybersecurity technology to insurance risk. I’ve talked with people from various standards committees who believe a combination of insurance risks plus board-level concern with those insurance risks will drive management to pay more attention to the situation.
So consider this report as part of a larger management strategy.
Proprietary claims data reveal the simple practices manufacturing cybersecurity leaders should implement to limit financial risk
The best responses to change and management are the search for the simplest. Not too simple, but definitely trying to defeat overly complex processes.
Manufacturing is currently the single most targeted industry for cyberattacks. Given their critical role in the modern interconnected economy and low tolerance for downtime, manufacturers have become a prime target for threat actors looking for bigger payouts. On April 28, 2026, Resilience released The State of Cybersecurity in Manufacturing to identify the key drivers of financial losses based on real claims data and security practices that deliver measurable reductions in financial risk across its manufacturing portfolio. The report offers manufacturing security leaders, risk managers, and brokers clear, evidence-based solutions grounded in real claims.
Key findings from Resilience’s manufacturing claims data include:
- Over 90% of total incurred losses in Resilience’s manufacturing portfolio were attributable to ransomware, despite ransomware making up only 12% of claim volume among manufacturers. This shows that when attacks do happen, the losses are severe.
- Phishing and transfer fraud accounted for 30% of manufacturing claims, showing that human error is still one of the leading causes of cyber disruption.
- About 26% of all portfolio losses came from an MFA misconfiguration as the point of failure. The single most expensive event in Resilience’s manufacturing portfolio, attributed to BlackCat, was enabled by misconfigured MFA.
- Wrongful data collection caused 12% of claims, driven primarily by website tracking and pixel-related litigation, rather than operational data collection from connected manufacturing systems.
- There are five specific, implementable security controls that manufacturers can undertake to meaningfully address material risk and harden their defenses against cyber threats.
Importantly, Resilience’s new data illustrates that the controls security leaders should implement aren’t complicated. Simple adjustments are all that’s needed to strengthen their posture against cyber risk.
What security controls deliver the highest ROI for manufacturing organizations? Based on Resilience’s analysis of manufacturing insurance claims data and financial risk modeling, five controls consistently delivered the most significant identified impact on financial exposure:
- Auditing and validating MFA deployment supports consistent enforcement across all accounts, elimination of bypass conditions, and proper configuration of conditional access policies.
- Strengthening vulnerability management for external-facing systems hardens organizations from software vulnerability exploited directly linked to expensive ransomware outcomes.
- Implementing procedural controls for financial transfers can protect against phishing and transfer fraud attacks that represent the most frequent claim activity in the portfolio. This is a strategic cost-saving practice, as the average transfer fraud event costs roughly ten times more than the average email compromise.
- Extending security requirements to vendors and supply chain partners is designed to help insulate manufacturers from a distinct cause of loss in the claims data. Manufacturers should extend their security requirements to critical vendors, including contractual MFA and patching requirements, continuous monitoring of vendor risk posture, and contingency plans for disruptions to critical suppliers.
- Cyber risk quantification and transfer support the translation of cybersecurity risk into financial language that resonates with CFOs and boards to assist in securing adequate investment. Resilience’s claims data provides a concrete basis for this conversation: ransomware dominates loss, a single point of failure (MFA misconfiguration) drives the largest share of exposure, and unpatched software is a direct line to the most expensive outcomes. These findings are intended to inform specific control investments and insurance coverage decisions.
by Gary Mintchell | Apr 29, 2026 | Robots
Robotics pioneer ABB has released a new cobot family. The news in brief:
- New, high-speed, higher payload PoWa cobot family meets need for industrial-grade performance in collaborative robotics, lowering the barrier to automation for both SMEs and large enterprises
- Payloads from 7kg to 30kg, best-in-class top speed of 5.8 m/s, longest reach and highest arm load on the market
- Powered by ABB OmniCore controller platform and seamlessly integrated with ABB Robotics’ suite of software tools
ABB Robotics is combining the flexibility of cobots with higher payloads and performance, with the launch of its new PoWa cobot family into the rapidly expanding global collaborative robot market, which ABB Robotics estimates will grow by 20 percent annually through to 2028.
“Cobots are growing significantly faster than traditional industrial robots, driven by demands from both small and midsized companies starting their automation journey as well as large enterprises,” said Andrea Cassoni, Head of Collaborative Robots at ABB Robotics. “These customers are seeking higher speeds and payloads, but also greater ease of use, and compact designs. Established manufacturers want to automate heavier, fast cycle applications, without the complexity and operational rigidity of traditional industrial robots. We are meeting these needs with the global launch of our high-speed PoWa cobot family – a name that symbolizes its powerful, industrial-grade performance in a compact collaborative robot form.”
The new PoWa family addresses a long‑standing gap in the market between traditional cobots, that often lack the speed and payload required for industrial applications, and conventional industrial robots, which are designed for highly specialized, large-scale automation environments, going beyond the needs of many collaborative tasks.
PoWa extends ABB Robotics’ comprehensive cobot offer with industrial-grade performance including six different payload categories, from 7kg to 30kg, the longest reach and highest arm load on the market and best-in-class top speed of up to 5.8 m/s.
Purpose-built for compact environments and ideally suited for applications such as high-speed machine tending, palletizing, screwdriving and arcwelding, PoWa enables manufacturers to automate heavier and faster processes, while maintaining the flexibility, ease of use and compact footprint of collaborative robotics.
PoWa cobots are exceptionally easy to use, through programmable buttons on the arm-side interface and no-code programming and are compatible with an extensive ecosystem of third-party accessories. PoWa can be unboxed and operational within an hour and enables seamless plug-and-play with a wide range of tools, blending industrial-grade connectivity and performance with collaborative robot flexibility.
Powered by the ABB OmniCore controller platform, the new PoWa cobots deliver best-in-class motion control, speed, and precision and can be integrated with ABB Robotics’ expanding suite of AI-powered software, including Robot Studio and Wizard Easy Programming, enabling intuitive programming, fast deployment and maximum uptime.
Ensuring collaborative robots can do more things, in more places, and do it faster, safer and smarter is part of ABB Robotics vision for more autonomous and versatile robotics (AVRTM). By developing a new generation of intelligent, flexible, adaptative, and collaborative multi-skilled robots, ABB Robotics furthers robots’ ability to learn, understand and plan independently, giving them greater autonomy and versatility.
