by Gary Mintchell | Dec 19, 2024 | Business
I think I recently wrote about how much I don’t care for year end recaps or next year prognoses. But, OK, I’m a sucker for a high level discussion of anticipated merger and acquisition deals in the coming year.
“The M&A outlook for Industrials is strong going into 2025, driven by improved macroeconomic influences, shifting policy regulations and divestitures to focus on core operations and strategic capital investment.”— Michelle Ritchie, Industrial Products Deals Leader
She continues in her report:
Industrial manufacturing deal activity expected to increase with continued focus in mid-market space.
We expect mergers and acquisitions (M&A) activity to increase in the industrial manufacturing sector in 2025, propelled by a more favorable economic environment and the conclusion of the US presidential election. Specific macro tailwinds include:
- Increased investor confidence following the election outcome
- A 75-basis-point reduction in interest rates since September 2024
- Inflation decreasing to approximately 3%
Companies are investing in several key manufacturing-related strategic areas, which are expected to accelerate M&A activity due to the time advantage of buying over building. These include:
- Digitization and technologically advanced equipment, which drive growth in fields such as robotics, automation equipment, sensors, monitoring and measurement devices. Companies are pursuing manufacturing efficiency gains and performance improvements to offset margin compression and support growth.
- Aging equipment and infrastructure, which create a need for replacement or refurbishment work, as well as the sale of parts and components for ongoing maintenance and repair needs.
- A continued focus on environmental sustainability, such as energy efficiency, reduced emissions and decarbonization, which drives the replacement of equipment and infrastructure with products that help companies meet regulatory standards, even if these are relaxed under the new administration.
- Government funding, which provides companies with resources to replace, upgrade or repair existing equipment and infrastructure.
by Gary Mintchell | Dec 18, 2024 | Business, News
The devil is in the data – harnessing AI and predictive technologies to drive resilience in an era of connectivity
These year-end predictions stories always seemed like some sort of journalist fill-in piece to me. I seldom did them as a magazine editor. And here. Although I have written two so far for other publications.
I have a good relationship with Fluke Reliability. Many years ago they participated in an innovative video podcast with me. They sent these thoughts. These topics have been subjects of thoughts all this year—data, supply chain, “digital transformation”, predictive maintenance, skilled labor. I present these as thoughts to try to go beyond the mundane to get you thinking about your 2025 plans.
2025 will bring new changes and challenges to the manufacturing industry, with a continued push toward digital transformation centered around data-driven decision-making and predictive maintenance. Businesses have been collecting data for years, but the real challenge is how to use that data to fuel future business opportunities, streamline operations, and enhance decision-making, which really drives competitive advantage.
There is no doubt that industry has faced many challenges this year, primarily driven by geopolitical and economic issues outside of our control. Yet, what we can control is where we focus our investment, and smart technology investments are critical to future-proofing organizations against uncertainty.
This year, the challenge will be not only keeping pace and embracing technological change but mitigating the risks of increasing labor shortages and supply chain disruptions.
Manufacturers Continue Moving Towards Digital Transformation
In recent years, we have observed a significant acceleration in the adoption of digital transformation within the manufacturing sector. This move has been characterized by a drive for competitiveness, efficiency, and advantage, which we anticipate will continue into 2025. This momentum shows no signs of slowing as the clear benefits of automation, AI, and IIoT are putting pressure on businesses to adopt new tools to stay ahead.
While organizations commonly embrace new technologies to increase reliability and break down information silos in manufacturing plants, we’re seeing this transformation go far beyond the floor. Technicians are using AI based analytics to troubleshoot a broken asset. C-suite executives are using advanced modeling and forecasting tools to assist them in deciding to repair or replace big-ticket equipment. We have witnessed a profound shift in the way companies are enabling using data-driven decision-making – spanning every role and becoming an integral part of every level of the enterprise. AI and advanced technology empower people across organizations to make smarter, faster, and more impactful decisions.
We are already seeing how Artificial intelligence (AI) can transform predictive maintenance and process optimization processes, enabling manufacturers to improve uptime and efficiency while reducing operational costs. Yet, beyond these gains, the ability to plan things like inventory, resources, and production is proving to be a game-changer for efficiency and the bottom line. Similarly, we’re also seeing how customers use digital twin technology as a strategic asset on their plant or factory floor. By creating real-time simulations and virtual replicas of plants or production lines, businesses can simulate, test, and refine new strategies before rolling them out in full.
The value lies in selecting the right use cases for each business. There is tremendous pressure on decision makers to adopt every new technological solution that comes onto the market to avoid falling behind their competitors. However, in order to achieve ROI, businesses must first be clear on their priorities and desired outcomes and align the adoption of new solutions to support these. That being said, there is a risk in being too cautious to adopt. Those who invested in pilot projects this year will likely be in the next phase of rollout in 2025—it’s a fine balance between making sure you have the right use case and keeping up to stay competitive.
Building Supply Chain Resilience Through Improved Management Practices Augmented by AI
The past few years haven’t seen much progress in mitigating global supply chain disruptions. Disruptions due to mis-matches in supply and demand have eased. However, these have replaced with increased risk to macro economic and geo political trends. We are facing increased turmoil with uncertainty around trade headwinds, raising concerns about overseas suppliers’ reliability. As a result, businesses are actively seeking ways to enhance adaptability and transparency within their supply chains. This includes reshoring operations, exploring alternative suppliers outside regions more susceptible to disruption, and adopting dual-source strategies for critical equipment.
Organizations are continuing to search for other solutions to tackle persistent supply chain issues, aiming to find the sweet spot between adaptability, transparency, and accessibility. The integration of advanced technologies such as AI and predictive maintenance into supply chain planning enables businesses to forecast demand for spare parts in advance and with greater precision. This facilitates a transition from “just in case” to “just in time” MRO inventory management. The result is not only a reduction in spare part inventory levels with the associated capital costs, it also helps minimize unplanned downtime.
Effective inventory management is a big focus here. More organizations are moving from spreadsheet- or pen-and-paper-based inventories to virtual storerooms that give an accurate, up-to-the-minute picture of supply levels. RFID technology and IIoT devices can provide real-time parts tracking. These tools provide workers with real-time visibility into supply levels, enabling them to search for parts quickly, see what’s on hand and where it’s located, and reserve it for their tasks, all from a mobile device. This also benefits multi-site facilities, which can share spare parts and reduce the uncertainty of relying on supply chain vendors. For example, our customer, Hexpol, has seen success by streamlining their supply chain by facilitating inter-plant sharing, circumventing long lead times between plants in neighboring states, and driving efficiency.
Artificial intelligence is also going to be critical for strengthening these ecosystems by making recommendations for restocking schedules so that companies have a strategic edge to maintain optimal inventory levels. Utilizing predictive insights, companies gain the foresight needed to restock replacement parts and avoid unexpected downtime due to shipment delays. It’s all about predictability, and every day gained from increased visibility into their operations is another day of avoiding downtime.
The Future of Skilled Labor Fueled by Technology
Skilled labor shortages continue to be an industry-wide challenge. Fortunately, technology’s value is coming to the fore and helping to bridge this gap. Businesses are increasingly turning to advanced technology to enhance productivity and reduce their reliance on a shrinking supply of skilled labor. Many of our customers are leveraging automation and advanced functionality within tools to help streamline tasks and increase output with fewer hands-on roles, particularly for repetitive tasks.
Fluke Reliability’s survey underscores this shift—98% of respondents consider AI a viable solution to the skills shortage, with 36% stating their primary motivation for implementing AI is to address this problem. While numerous industry use cases support this, we have seen some of the strongest emerge within manufacturing, where pilot projects are driving newfound efficiency and value. By increasing automation, organizations are reducing the demand on employees, streamlining tasks, and reducing the reliance on hands-on roles for repetitive or dangerous jobs.
For example, a common challenge facing our customers is how to efficiently assets across the plant floor in single facilities or cross-site operations with a smaller, potentially lower-skilled workforce. Remote condition monitoring solutions powered by AI analytics coupled with wireless sensor technology enables a smaller group of technicians to maintain visibility into asset health that would have previously required a large number of distributed boots on the ground. This approach, enabled by AI-powered analytics and condition monitoring, makes it possible for expertise-constrained operations to adopt a data-based maintenance strategy and deliver benefits in uptime and efficiency. It’s a win-win.
Additionally, emerging technologies like VR and AR capabilities are reshaping how we train and upskill the workforce. While there are still questions about the safety of AR on the factory floor, it presents an opportunity for off-floor simulation, helping people become familiar with operations in a risk-free environment before progressing to the real task at hand. Less intensive, we see an opportunity for GenAI to bridge the knowledge gap as a co-pilot to walk less experienced maintenance technicians through more complex fixes.
As an industry, we need to focus on what we can control to fix the skills shortage: automating processes through AI to relieve teams, adopting new technology or training to upskill existing employees, and ensuring knowledge transfer from those set to retire. These steps, coupled with investing in the next generation, are steps most businesses have within their control—it’s our collective job to protect the future of the industry.
Predictive Maintenance Practices to Continue Moving Sustainability Initiatives Forward
Predictive maintenance is increasingly being discussed in conversations around sustainable operations. It optimizes equipment for reliability and environmental impact. By enhancing renewable energy asset availability, extending equipment lifespans, and lowering emissions through improved energy efficiency, predictive maintenance supports companies’ ESG (Environmental, Social & Governance) goals. With customers placing more emphasis on sustainable operations, this strategy enlists operational reliability in support of global environmental priorities.
The current economic climate has amplified the focus on efficiency and maintaining equipment rather than replacing it. More businesses want to automate their operations with tactics like condition monitoring and connected reliability. Similarly, as organizational PdM initiatives build momentum, companies collect more data and effectively gain more knowledge about their equipment and its health. The next step, and the real opportunity, lies in analyzing the data, which AI can do with ease. Using an AI-powered diagnostic engine can compare new data to historical data to detect issues within an asset before it fails — and even make recommendations for how to fix the problem, all of which contribute positively to sustainable operations.
Accessibility is improving, too. Advances in technology, such as wireless sensors, have made continuous monitoring more affordable, allowing for broader asset coverage and improved efficiency. This approach cuts energy use, reduces waste, and lowers costs, demonstrating that sustainability-focused maintenance can drive both environmental and economic benefits.
Conclusion
This new era of connectivity will enable data to flow seamlessly between departments, orchestrated by intelligent algorithms that analyze information in real time. Imagine a company where predictive analytics, powered by AI, continuously forecasts demand, identifies problems before they escalate, and swiftly adapts to shifts in market conditions or supply chain volatility.
In 2025, economic uncertainty will continue as companies look into an unclear future, including inflation, tariffs, and continued talent shortages. Many organizations are slowing their investments in new physical assets and instead shifting their focus to maintaining current equipment with AI-enabled tools and predictive maintenance. By using these methods, companies will reduce their carbon footprint by making technology investments that are both financially economical and environmentally impactful.
by Gary Mintchell | Dec 12, 2024 | Business, Commentary, News
John Gruber’s Daring Fireball consistently provides a perceptive view into the tech industry. This post dives into the situation at Intel and how Pat Gelsinger was forced out.
The Verge’s Sean Hollister penned an excellent high-level summary of how Pat Gelsinger wound up getting forced out of Intel, “What Happened to Intel?”. A wee bit of pussyfooting here, though, caught my eye:
Just how bad was it before Gelsinger took the top job?
Not great! There were bad bets, multiple generations of delayed chips, quality assurance issues, and then Apple decided to abandon Intel in favor of its homegrown Arm-based chips — which turned out to be good, seriously showing up Intel in the laptop performance and battery life realms. We wrote all about it in “The summer Intel fell behind.”
Intel had earlier misses, too: the company long regretted its decision not to put Intel inside the iPhone, and it failed to execute on phone chips for Android handsets as well. It arguably missed the boat on the entire mobile revolution.
Gruber’s article continues through a litany of Intel misses. Mobile market, ARM chips, GPUs, chips for AI.
He concludes:
Intel never should have been blithe to the threat. The company’s longtime CEO and chairman (and employee #3) Andy Grove titled his autobiography Only the Paranoid Survive. The full passage from which he drew the title:
Business success contains the seeds of its own destruction. Success breeds complacency. Complacency breeds failure. Only the paranoid survive.
Grove retired as CEO in 1998 and as chairman in 2005. It’s as though no one at Intel after him had listened to a word he said. Grove’s words don’t read merely as advice — they read today as a postmortem synopsis for Intel’s own precipitous decline over the last 20 years.
I’m wondering how much the disease at Intel is similar to the disease that struck Boeing. Engineering companies run by finance people. My management training included the maxim to never let companies be run by sales (a problem in the trade media, by the way). Maybe another maxim would be never let the finance department run the company?
by Gary Mintchell | Dec 10, 2024 | Business, Commentary, News
One of my trusted news sources is News Items from John Ellis. Today’s email contained an item—revolution in global manufacturing—that grabbed my immediate attention.
This regards China’s long term investment in electric vehicles that is now paying off. I remain convinced that one of the many reasons Elon Musk decided to throw whole-hearted support to Donald Trump was Trump’s belief in using tariffs to protect American industry. A significant one could be Tesla—the EV company under threat from China’s BYD.
Beyond Tesla lie many other American car companies that have been the foundation of our manufacturing health for a century. The other American car companies, bowing to short-term financial pressure, are scaling back on EV manufacturing just at the time China is poised to dominate the market.
Ellis quotes (requires subscription):
As (a) New York Times story makes clear, China now has an incredible—and I would argue unprecedented—capacity to supply over half the global market for cars, which is typically around 90 million cars a year.
China’s internal market is around 25 million cars, and not really growing—so rising domestic EV sales progressively frees up internal combustion engine capacity for export. Domestic demand for traditional cars is likely to be well under 10 million cars next year given the enormous shift toward EVs now underway inside China.
Put differently, China currently has the capacity to produce over two times its own domestic demand and is adding to that capacity quickly thanks to the rapid expansion of its electric vehicle sector. It thus has almost unlimited potential capacity to export.*
That sets the scale for a potential revolution in global manufacturing.
The story is partially derived from an article in The New York Times:
China is a leader in the transition to electric vehicles and it exports more of them than any other country. Chinese brands like BYD are becoming known worldwide for offering advanced electric cars at the most competitive prices. And as Chinese drivers have shifted rapidly to electric vehicles, demand for gasoline-powered cars in China has plunged and many are being exported instead.
Interesting that while waiting for the critical mass for the EV market, China is using its manufacturing capacity for internal combustion cars to export these.
But China’s trading partners say that China’s exports of both electric and gasoline-powered cars imperil millions of jobs and threaten major companies. Earlier this year, the United States and the European Union put significant new tariffs on electric cars from China. Governments are concerned because the auto industry plays a big role in national security, producing tanks, armored personnel carriers, freight trucks and other vehicles.
Two years of my undergraduate work was dominated by the study of international politics—how nations relate and interact with each other. I’m consistently amazed by the lack of understanding by US politicians elected to high office who do not seem to grasp the basics. For example, Trump seemed to think that the US could employ tariffs to bend other countries to our will. But other countries can employ the same tools back to us.
What’s more, China has used steep tariffs and other taxes as a barrier to car imports, so that practically all of the cars sold in China are made in China.
Relationships are complicated—both country-to-country as well as person-to-person.
by Gary Mintchell | Dec 2, 2024 | Business, News
I’ve been reading M.G. Siegler for years. Ever since the early days of TechCrunch. I saw this morning in his Spyglass Digest that Pat Gelsinger is suddenly out at Intel. This from Business Wire.
Intel has missed several market movements. Mobile and AI to name two. Their manufacturing processes began to lag several years ago. Gelsinger was an Intel veteran who had done well at his last gig. It was hoped he could stir things up. This latest loss from the Biden Administration’s Chips Act probably was the proverbial straw.
Business Wire:
Intel Corporation (NASDAQ: INTC) today announced that CEO Pat Gelsinger retired from the company after a distinguished 40-plus-year career and has stepped down from the board of directors, effective Dec. 1, 2024.
Intel has named two senior leaders, David Zinsner and Michelle (MJ) Johnston Holthaus, as interim co-chief executive officers while the board of directors conducts a search for a new CEO. Zinsner is executive vice president and chief financial officer, and Holthaus has been appointed to the newly created position of CEO of Intel Products, a group that encompasses the company’s Client Computing Group (CCG), Data Center and AI Group (DCAI) and Network and Edge Group (NEX). Frank Yeary, independent chair of the board of Intel, will become interim executive chair during the period of transition. Intel Foundry leadership structure remains unchanged.
by Gary Mintchell | Nov 21, 2024 | Business, Commentary, News
Each year for perhaps 20 years, Control magazine along with the ARC Advisory Group publishes a list of the top 50 automation suppliers globally and in North America in terms of revenue. This year’s list is introduced this way.
The largest global and North American automation suppliers report artificial intelligence (AI), sustainability, advanced computing and services drive growth.
The technologies have advanced along with the general advance in compute power, standardized networking (including fieldbuses), and visualization.
What I notice is the stability of the top 50. The leaders are mostly still the leaders with the exceptions only of a couple companies that have been on acquisition paths. You still have Siemens, ABB, Rockwell, Honeywell, Emerson, and Schneider Electric.
The market has matured. Some technologies have, also. Profinet, Ethernet/IP, HART are all stable and ubiquitous. There are also CCLink and EtherCat in certain areas.
I am writing this while collecting thoughts and observations at Rockwell Automation’s Automation Fair. This opportunity affords conversations with companies other than Rockwell Automation to assess the state of the industry.
One point stands out—the state of the market in North America. I notice that while Emerson and Rockwell Automation still rock, Siemens, ABB, and even Honeywell show small sales while Yokogawa is barely a blip. This coincides with the undertone talk amongst people at the various non-Rockwell stands here in Anaheim about the past year being slow.
All this is merely interesting. I’m sure that when you make automation procurement decisions, it will be based on far more than industry rank.
