Best of LinkedIn: Connected Tools & Equipment CW 41/ 42

00:00:00: provided by Thomas Allgaier and Frenus, based on the most relevant LinkedIn posts about connected tools in equipment.

00:00:05: In calendar weeks.

00:00:06: forty one and forty two, Fren us is a B to be market research company that supports enterprises in the power tool sector with building feature-by-feature competitive intelligence That shows exactly how their product stacks up against the competition.

00:00:19: you can find more info in the description.

00:00:22: You know imagine your stepping onto a commercial job site say three years from now.

00:00:27: You're walking past a massive newly installed water system and suddenly a pipe bursts.

00:00:33: Oh man, yeah worse nightmare right there Right

00:00:36: And I mean in the past that moment just kicked off this massive liability blame game.

00:00:41: The general contractor blames the plumber...the plumber blames..the pipe manufacturer....and then the manufacturer blames ...the tool used to crimp the pipe.

00:00:48: Everyone just points fingers

00:00:50: Exactly.

00:00:51: But today That dynamic is totally vanishing.

00:00:55: A site manager can pull up a digital ledger and basically prove that the exact press tool that sealed that specific joint was perfectly calibrated.

00:01:03: Wow!

00:01:04: Yeah, shows it applied the exact specified pressure...and boom It shifts the liability instantly.

00:01:09: I mean..it is total paradigm shift And honestly That's exactly what we are focusing on for this deep dive.

00:01:16: Definitely We're taking all of the noise from LinkedIn specifically looking at absolute top trends in connected tools & equipment.

00:01:24: We want to break down what it actually means for you, the people running smart build and manufacturing operations.

00:01:29: Yeah cutting through the fluff

00:01:30: exactly.

00:01:31: So here is the roadmap for today.

00:01:34: we're moving from The foundation of the stationary factory floor straight into the hands Of the workers with cordless platform expansion And finally will zoom out To see how massive fleets of these smart tools are Actually being managed You know without just drowning in data.

00:01:49: It makes a lot of sense to start on the factory floor honestly because that really is The Foundation, right?

00:01:54: I mean if you do not have an accurate read On the health Of your heavy stationary equipment Your production schedule Is basically Just A wishlist.

00:02:02: Yeah!

00:02:02: A total guess

00:02:03: Right?

00:02:04: Historically maintenance was largely calendar based.

00:02:07: So every six months You swap a belt.

00:02:10: Or y'know Every three thousand hours You grease a bearing

00:02:13: Regardless Whether the bearing actually NEEDS grease

00:02:15: Right?!

00:02:15: You just follow the manual

00:02:16: which is incredibly inefficient.

00:02:18: So the industry shifted to condition based maintenance, you slap a sensor on the machine and you wait for the machine to tell you it's hurting.

00:02:25: make sense

00:02:27: but The Post were analyzing show this major maturation of space.

00:02:31: A few years ago everyone was just celebrating getting sensors onto machines at all?

00:02:35: yeah Just having that hardware

00:02:37: Yeah.

00:02:37: But now...the conversation is violently pivoted away from.

00:02:40: just like sensor availability Now it's heavily focused on data quality, installation discipline and using software that actually works with the data you already have in place.

00:02:51: So its no longer really a hardware bottleneck.

00:02:53: I mean getting sensors easy.

00:02:55: The real bottleneck is whether this sensor is telling truth?

00:02:58: It is massive problem!

00:03:03: perfectly mimics bad equipment.

00:03:06: Oh, interesting!

00:03:06: Yeah like if your vibration sensor is mounted loosely or the data resolution it's just poor.

00:03:11: Your remote dashboard might start flashing red.

00:03:14: It tells you maintenance team a hundred thousand dollar lathe this about to fail.

00:03:17: So they shut down?

00:03:18: Exactly They tear their machine down and lose full day of production And find absolutely nothing wrong.

00:03:24: That is brutal.

00:03:26: Or conversely The dash board glows green while critical component actively tearing itself apart.

00:03:32: But how does a sensor miss... I mean, if it's bolted right to the machine.

00:03:36: How does it miss a catastrophic failure?

00:03:38: Does this just go offline?

00:03:40: Not at all!

00:03:41: It stays perfectly online but its looking for the wrong kind of math.

00:03:45: Let us get into mechanics because is really critical to understand.

00:03:48: Yeah let s do it

00:03:49: A lot.

00:03:49: basic condition monitoring relies on FFT which is fast.

00:03:52: Fourier transform vibration analysis.

00:03:55: Okay.

00:03:56: And what FFT does is it takes all the complex vibrations of a machine, and it averages them out over time to give you a clean readable spectrum.

00:04:04: Like taking the sound off an entire orchestra and just averaging up volume?

00:04:09: That's really good way to look at it!

00:04:11: But imagine during that orchestral performance someone drops heavy metal music stand on the floor

00:04:16: Right...a huge crash.

00:04:17: Exactly It's sharp violent spike noise.

00:04:21: If you average audio over five minute window basically get smoothed out.

00:04:27: Oh wow!

00:04:28: Yeah, you might not even notice it on a graph.

00:04:31: and the exact same thing happens with a failing bearing.

00:04:34: when a bearing race first starts to crack It creates a very brief sharp impact every single time a roller hits

00:04:41: but The FFT just hides it.

00:04:43: yes FFT analysis will smooth that micro-impact right out into the average.

00:04:48: So your dashboard says your average vibration is perfectly normal But the bearing is taking a hammer blow like Twenty times a second.

00:04:56: Yes, exactly You only catch those worsening bearing impacts if your system is looking at the raw time waveform data

00:05:03: The actual unfiltered spikes

00:05:05: Right in real-time.

00:05:08: And this why data quality's suddenly taking center stage.

00:05:10: you can't just throw cheap sensors at machine and expect predictive magic

00:05:15: Which totally explains what we are seeing from companies like Schaeffler.

00:05:19: right they were highlighted for their optimized system?

00:05:22: And they are now adding AI detection, specifically for RPM and under lubrication right into affordable sensors.

00:05:29: They're basically taking that higher level complex analysis the stuff that catches the dropped music stand... ...and building it directly in to accessible hardware.

00:05:38: You know if you don't want to buy new hardware?

00:05:40: The software side is catching up just as fast.

00:05:42: Oh really?

00:05:43: Yeah,

00:05:44: Iconics Genesis was highlighted heavily in the post this week.

00:05:47: they are a software solution that delivers predictive maintenance using the equipment.

00:05:51: data of facility already has

00:05:53: oh so no new sensors

00:05:55: exactly.

00:05:56: they aren't asking you to rip and replace your sensors They are just pulling higher quality waveform level insights from the architecture You've already paid to install.

00:06:04: That's huge.

00:06:05: And it is about scale, too.

00:06:07: I mean think of the example shared by Control-C in this source material...

00:06:11: Oh!

00:06:11: The massive deployment?

00:06:12: Yeah they are deploying sensor based predictive maintenance across a one hundred thirty thousand square foot facility At one hundred and thirty thousand sq feet.

00:06:20: if your sensors throwing false positives because their mounted poorly you don't just have a maintenance problem You've got cultural problems.

00:06:27: Alert fatigue Is very real at that scale.

00:06:31: If system cries wolf three times Your floor technicians will just start ignoring the tablets entirely.

00:06:36: They go back to trusting their ears in a grease gun?

00:06:39: Exactly!

00:06:40: I want

00:06:40: pushback on this, though... It feels like buying a flagship smartwatch with all biological sensors but never actually looking at dashboard so you keep eating junk food anyway.

00:06:52: We have all of these incredible data yet sources are still citing shop-floor engagement and real communication as primary reason.

00:07:00: high tech maintenance programs fail.

00:07:02: Yeah that's true.

00:07:03: Why is the human element still breaking down when math's so good?

00:07:06: Because, at end of day a dashboard cannot turn to wrench.

00:07:09: Fair point!

00:07:10: You can have AI perfectly detecting and dry bearing but if data analyst sitting in an office somewhere doesn't have trusting engaged relationship with technician walking shop floor... The work order just gets de-prioritized

00:07:23: And machine goes down anyway.

00:07:24: Right!

00:07:25: Diagnostic technology largely solved Operational workflow between digital layer & physical.

00:07:32: Well, that is where the friction is.

00:07:34: Which brings us perfectly to the technicians themselves right?

00:07:36: And the tools they are actually holding in their hands To do that physical work?

00:07:40: Oh absolutely

00:07:41: If stationary machines Are getting this smart The mobile tools fixing them have to evolve too.

00:07:46: We're seeing a massive expansion In cordless platforms But it's moving way beyond.

00:07:52: just like swapping A power cord for battery.

00:07:54: It really Is total redefinition of what hand tool even is.

00:07:59: The expansion is aggressive in two specific areas right now.

00:08:02: Okay, what are they?

00:08:03: Pushing into ultra heavy-duty territory and tying the physical action of the tool directly to digital traceability.

00:08:10: Let's start with the heavy duty side because Hilti Neuron was a major focus this week.

00:08:14: Oh yeah huge push.

00:08:15: They are pushing battery platforms into spaces that used to strictly belong to combustion engines like the standout.

00:08:21: example Was their DSH.

00:08:23: nine hundred dash twenty two battery-powered saw.

00:08:27: that delivers the exact performance of a ninety CC gas saw.

00:08:31: And anyone who works in heavy construction knows, that a ninety cc gassaw is an absolute beast.

00:08:37: Yeah

00:08:38: I mean it's used for cutting concrete Heavy masonry thick steel The torque required to prevent a blade from binding In solid concrete.

00:08:46: It just immense.

00:08:48: But i have to push back here though.

00:08:50: Anyone who has run tools hard knows that batteries hate heat and they really hate sustained heavy load.

00:08:56: Right, They thermal out.

00:08:58: Exactly so.

00:08:59: a battery replacing a ninety CC saw.

00:09:01: how are they achieving?

00:09:02: That sustained output without the thermal limits of the cells?

00:09:05: just you know melting The casing or shutting the tool down in three minutes.

00:09:10: well that is the big engineering leap here.

00:09:12: It's not Just about strapping bigger Cells together with some tape.

00:09:15: Right.

00:09:16: The platform architecture, like how the tool manages thermal offloading and how it dynamically draws power across multiple battery interfaces at once?

00:09:25: It has reached a point where can handle sustained high-amp draw without thermal runaway.

00:09:31: Oh wow!

00:09:32: And...the operational benefit on this site is just massive.

00:09:35: You completely eliminate mixing two stroke fuel.

00:09:38: you have zero exhaust fumes in enclosed spaces which is huge for safety.

00:09:42: Yeah definitely and the vibration profile drops significantly.

00:09:46: By the way, real quick before we dive into the data side of these tools if you want to stay ahead of industry shifts like this make sure you hit subscribe so you catch all our future deep dives.

00:09:55: We are constantly tracking how these platforms are evolving

00:09:58: And they are evolving fast believe me.

00:10:01: Hilti is also rolling out the PLT-Fourhundred layout tool.

00:10:04: Okay This takes that heavy duty site work and pairs it with precision AI target tracking.

00:10:13: Milwaukee is pushing the exact same boundaries.

00:10:15: In The Source Material, they highlighted the M-A-Teen Fuel Roll Groover.

00:10:19: Oh right

00:10:20: For anyone outside of commercial plumbing a roll grover Is basically machine that cold forms A groove into end Of steel pipe so you can attach mechanical coupling.

00:10:29: It replaces having to thread or weld the pipe

00:10:31: Right which takes forever

00:10:32: Exactly and usually That's heavy stationary Machine.

00:10:36: but Milwaukee just made first portable cordless one.

00:10:40: Think about workflow change there.

00:10:42: Instead of measuring a pipe, walking it down along hallway to stationary grooving machine.

00:10:47: Grooving and then carrying all the way back to scissor lift

00:10:50: which is just wasted labor Exactly!

00:10:53: Now a pie fitter can prep the pipe right at point installation.

00:10:57: The efficiency gain is staggering.

00:10:59: But the Milwaukee tool that really underscores the traceability shift we talked about is the M-twelve one key force logic press tool.

00:11:06: Yes Press

00:11:07: tools join pipes by crushing a fitting around them with incredible force, but this specific m-twelfth tool doesn't just do the crimp.

00:11:14: it records every single press It makes right into a digital log.

00:11:18: and This goes right back to your intro hook About the bursting pipe.

00:11:21: exactly

00:11:22: when the tool records Every single actuation.

00:11:25: you have officially moved from mechanical labor to digital compliance.

00:11:30: That tool is logging the date, time and exact pressure achieved... ...and whether this cycle actually completed

00:11:35: successfully.".

00:11:36: It essentially turns a wrench into a notary public?

00:11:39: "...It really

00:11:39: does!".

00:11:40: It completely changes risk profile of contractor!

00:11:43: You aren't just relying on visual inspection by a foreman anymore….

00:11:46: Right.

00:11:47: …you literally hand client-to-data base proving every single joint meets manufacturer's spec.

00:11:53: Incredible.

00:11:54: This intelligence is spreading across all trades.

00:11:56: Bosch just launched the GLK-twelve volt and eighteen volt cordless soldering irons.

00:12:01: So bringing mobility to precision electronics work, right?

00:12:04: Yeah

00:12:04: And DeWalt is heavily targeting professional landscapers with battery powered commercial outdoor equipment

00:12:09: in.

00:12:09: The landscaping push makes total sense You know when you think about urban noise ordinances and a huge push for zero emissions on city centers.

00:12:17: Definitely.

00:12:18: but I think the most fascinating example of tool intelligence was that aircraft maintenance post.

00:12:23: oh the ratchets.

00:12:24: Yeah, it noted that cordless ratchets used by aviation technicians are now being judged on their control parameters rather than just their peak catalog torque.

00:12:32: Because I mean stripping a bolt onto a garden gate is annoying but stripping the bolt upon titanium aerospace component...that's catastrophic delay!

00:12:42: Right and costs thousands of dollars.

00:12:44: so how they actually getting that control?

00:12:47: It's the beauty of brushless electric motors.

00:12:49: you can program the torque curve via software.

00:12:52: Okay

00:12:53: See, a pneumatic air tool just hits with brute force based on the air pressure from the compressor.

00:12:58: But a smart electric ratchet can be programmed so that the tool physically cannot over-torque delicate fastener

00:13:04: Even if you hold trigger down?

00:13:06: Yep regardless of how hard the technician squeezes the trigger The tool basically acts as an active physical safeguard.

00:13:14: The market adoption is playing out exactly what we would expect too.

00:13:17: TTI currently leads the global cordless assembly fastening tools market with a massive twenty four point forty-four percent share.

00:13:24: They are dominating.

00:13:25: they really Are but zooming out it kind of feels like we're watching The power tool industry go through its smartphone moment.

00:13:32: How do you mean?

00:13:33: well, twenty years ago?

00:13:34: A mobile phone just cut the cord from the wall But then became this massive data ecosystem device

00:13:40: all right

00:13:41: Are contractors today buying a tool that joins pipes or are they buying data collection node just happens to squeeze metal?

00:13:48: They're absolutely buying the data.

00:13:50: I mean, it was just physical interface for compliance ledger.

00:13:53: now Wow

00:13:55: The value of liability protection is very quickly surpassing the mechanical action itself.

00:14:02: That creates massive new headache If your factory floor condition monitoring thousands of data points and your workers have traceable heavy-duty smart tools that log every single trigger pull.

00:14:15: How does a site manager actually keep track of twenty five thousand different data nodes without just drowning in spreadsheets an alert fatigue?

00:14:23: Well, That is the third end final trend.

00:14:25: we are seeing The rise of the operational ecosystem.

00:14:29: Okay

00:14:30: If you look at commercial activity right now like the acquisitions, the distribution agreements.

00:14:35: They are aggressively concentrating on fleet and connected asset tracking

00:14:40: The scale of these moves is honestly hard to comprehend.

00:14:43: Look at Clipboard.

00:14:43: they recently acquired LynxUp.

00:14:46: What does

00:14:46: a software acquisition that actually look like?

00:14:49: On-the-ground

00:14:50: It means clipboard absorbed two hundred forty thousand connected devices into their ecosystem literally overnight.

00:14:56: Good grief

00:14:58: Yeah That's massive consolidation of tracking data.

00:15:01: How does an interface even handle two hundred forty thousand devices?

00:15:04: You can't just look at a map with a quarter million red dots on it.

00:15:08: You really can, the ecosystem has to rely entirely on exception based reporting.

00:15:12: and

00:15:12: what Does that mean?

00:15:13: The

00:15:13: software doesn't tell you where all your tools are.

00:15:16: It only alerts you when a tool leaves A geofence job site unexpectedly or say When a tool is past due for its annual calibration.

00:15:24: Oh I see

00:15:25: the software has To filter the noise so the manager Only sees the anomalies.

00:15:30: And we are seeing end users adopt this at an incredible rate.

00:15:34: Like Asplend is adopting SEMSARA AI dash cams for connected vehicle and equipment tracking, huge

00:15:39: move...

00:15:39: ...and Hilti just signed a five-year partnership with SpeedyHire?

00:15:43: That agreement alone covers twenty-five thousand hilti assets

00:15:46: because you absolutely cannot manage a fleet of twenty-five thousand heavy duty tools without a centralized intelligence software layer.

00:15:53: right And it's not just the massive national fleets either.

00:15:56: We are seeing this demand pushed down to local and regional distribution levels.

00:16:00: Oh, really?

00:16:00: Yeah.

00:16:01: Plumb-based Bournemouth is beginning a Milwaukee partnership that heavily features a broad range of M-Eighteen and M-Twelve connected tools.

00:16:09: Another great regional example as Southern Power Tools.

00:16:12: they're in deep discussions with DeWalt specifically about tool asset tracking compliance and something called HAVS Hand Arm Vibration Syndrome.

00:16:21: We really need to unpack halves because it perfectly connects everything we've discussed today.

00:16:24: Yeah, let's do it.

00:16:26: Hand arm vibration syndrome is a severe occupational hazard.

00:16:31: if you spend eight hours a day running A concrete breaker or heavy drill the vibration physically damages The blood vessels and nerves in your hands.

00:16:38: Wow yeah at least a permanent loss of sensation sometimes called white finger.

00:16:42: Traditionally preventing that was just guesswork.

00:16:44: right like a site manager with a stopwatch on a clipboard trying Guess how many hours a guy had been on the jackhammer?

00:16:50: Exactly.

00:16:51: It was incredibly inaccurate, but with an ecosystem of connected tools The tool itself logs the exact trigger time.

00:16:58: Oh man.

00:16:59: furthermore it knows its own vibration profile.

00:17:02: So the operational ecosystem tracks the cumulative vibration exposure for this specific worker holding the tool.

00:17:09: that is wild

00:17:10: And it automatically flags a supervisor, or can even lock the tool out entirely when that worker has reached their safe legal exposure limit for the day.

00:17:18: So its automated worker safety driven entirely by fleet

00:17:22: tracking?

00:17:23: Exactly!

00:17:23: That is incredible.

00:17:24: and this data-driven management isn't just happening in mud on job sites... It's also happening inside precision manufacturing environments too.

00:17:32: ANBs connected tool room systems were highlighted to enable full traceability, presetting & balancing.

00:17:39: Let's explain what presetting and balancing actually means in a tool room because it ties directly back to our first theme of condition monitoring.

00:17:47: Okay,

00:17:47: when you put a cutting tool like heavy end mill into a CNC machine if the mass of that tool isn't perfectly centered It wobbles at high speeds.

00:17:57: That wobble is called run out.

00:17:59: And uh What twenty thousand rpm.

00:18:02: even microscopic wobble creates a ton of vibration.

00:18:05: exactly.

00:18:07: And what happens when you create vibration on a machine spindle?

00:18:10: You trigger the very condition monitoring sensors we talked about at the beginning of the deep dive.

00:18:16: Oh!

00:18:16: The FFT and time waveform data gets totally muddied, but AMB's connected systems ensure that tool is perfectly balanced... ...and its precise dimensions are sent digitally to the machine before it ever makes a cut.

00:18:28: So it's closed loop.

00:18:29: It is completely closed-loop of data reducing wear in eliminating those false sensor alarms.

00:18:35: It is a totally different way of looking at hardware.

00:18:38: Now, instead of just buying a drill or an end mill we are deploying edge computing nodes into a managed ecosystem.

00:18:44: Edge Computing IS the exact right term.

00:18:46: The tool isn't just a dumb piece of metal sending raw data to the cloud To ask what it should do.

00:18:51: Right...The tool itself Is processing the torque curve Its analyzing battery heat And its making micro adjustments locally on the EDGE Of network.

00:19:01: You know, there was an insight in the source material from Jinhua Zhao regarding autonomous vehicle fleets that I think perfectly frames where the smart build industry is heading right now.

00:19:09: Oh The cost breakdown?

00:19:10: Yeah

00:19:11: He pointed out that with autonomous fleets the physical hardware of the vehicle itself only represents thirty to forty percent Of the total five-year cost.

00:19:19: Right!

00:19:20: The remaining sixty to seventy percent of the cost and effort Is the operational ecosystem.

00:19:23: you Know the staging tracking maintaining and charging.

00:19:27: The smart tools industry seems to be waking up to that exact same reality.

00:19:31: Managing the library is now significantly more expensive and critical than the books themselves.

00:19:36: It really is the ultimate realization for fleet managers right now.

00:19:40: Buying a two thousand dollars SmartPress tool, it's actually the cheap part.

00:19:44: Yeah!

00:19:44: The real investment And the real competitive advantage Is the operational discipline.

00:19:49: Do you have the software to track where it is?

00:19:52: do You know who is actually using it

00:19:54: Right...is

00:19:54: the calibration status Up-to-date And is it successfully beaming that compliance data back to your ledger so you don't get sued?

00:20:02: The library infrastructure is absolutely where construction and manufacturing companies are either winning or losing the war.

00:20:09: Which leaves us with a fascinating operational dilemma.

00:20:11: as these ecosystems mature, With tools recording every single trigger pull logging Every minute of vibration exposure an AI perfectly mapping the efficiency Of every cut we have achieved total operational transparency We Have.

00:20:26: But how does the veteran workforce react to this?

00:20:29: See that is the friction point.

00:20:31: No one wants to talk about.

00:20:32: from a management perspective.

00:20:34: This is ultimate.

00:20:34: liability protection and safety

00:20:36: sure,

00:20:37: but if you are a skilled pipe fitter who has been doing this for twenty years You might look at a tool that tracks your every movement limits Your trigger time and logs your exact location.

00:20:47: well not as a safety device But it's surveillance

00:20:51: big brother in a toolbox.

00:20:52: exactly.

00:20:53: Will veteran technicians embrace these tools as empowering, or will they reject the ecosystem because they feel micromanaged by their very wrench that are holding?

00:21:02: That adoption curve is going

00:21:17: to dictate.