42 posts tagged with "Industrial IoT"

Sustainability in manufacturing isn't a PR initiative anymore — it's a business requirement. Customers demand it, regulators mandate it, and energy costs make it financially necessary. The EU's Carbon Border Adjustment Mechanism (CBAM) begins full enforcement in 2026. The SEC's climate disclosure rules require public companies to report Scope 1 and Scope 2 emissions. Major OEMs like Toyota, BMW, and Apple are pushing emissions reduction requirements down their entire supply chain.

For manufacturers, the question has shifted from "Should we care about sustainability?" to "How do we actually measure and reduce our environmental impact?" The answer, increasingly, is Industrial IoT. Not because IIoT is a sustainability technology — it isn't, inherently — but because you can't reduce what you can't measure, and IIoT provides the measurement infrastructure that makes sustainability initiatives actionable.

Running a single plastics plant is complex enough. When you scale to two, three, or ten facilities — each with dozens of injection molding presses, extruders, blow molding machines, and secondary operations — complexity doesn't just increase. It multiplies.

The plant manager at your Wisconsin facility is tracking cycle times on 40 injection presses. Your Texas extrusion site runs 15 lines around the clock. Your Mexico plant handles secondary operations — trimming, assembly, pad printing. Each facility has its own tribal knowledge, its own definition of "good," and its own spreadsheets tracking downtime.

This is where fleet management becomes the difference between scaling successfully and drowning in operational blind spots.

A short shot costs you a part. A flash defect costs you a part and a mold repair. A hydraulic blowout costs you a shift. But the data that predicted every one of these failures was sitting in your PLC registers 30 minutes before they happened — barrel zone 3 creeping 8°F above setpoint, hydraulic pressure trending 200 PSI below normal, cooling water flow dropping 15% from baseline.

The difference between catching a defect and shipping a defect is whether your monitoring system screams at the right time. Smart alarms for plastics processing aren't just about knowing when something broke — they're about knowing when something is about to break.

Every plastics manufacturer knows downtime. What most don't know is exactly how much it's costing them — or where those hours are actually going. A mold change that should take 45 minutes stretches to 90. A hydraulic seal failure on a 500-ton press takes out three shifts. A purging procedure that was supposed to be "quick" turns into a four-hour color change nightmare.

The difference between plastics shops running at 75% OEE and those hitting 85%+ isn't better machines — it's better downtime visibility. When you can categorize, measure, and analyze every minute of lost production, you stop guessing and start systematically eliminating waste.

Every factory floor generates thousands of data points every second — cycle counts, temperatures, pressures, alarm states, energy consumption, material flow, machine status. The vast majority of this data is thrown away. Factory floor analytics is the discipline of capturing that data, extracting intelligence from it, and using that intelligence to make better manufacturing decisions. Here's how it works in practice.

Ignition by Inductive Automation has been a favorite among manufacturing engineers for over a decade — a powerful, developer-friendly SCADA platform with an unlimited licensing model. MachineCDN is a cloud-native IIoT platform that connects to PLCs in minutes. Both give you visibility into your machines, but they represent two different eras of industrial software. Here's what matters for your decision.

Tulip and MachineCDN both serve manufacturers, but they solve fundamentally different problems. Tulip is a no-code platform for building custom manufacturing apps. MachineCDN is a protocol-native IIoT platform for machine monitoring, predictive maintenance, and factory intelligence. Understanding where each platform excels — and where it doesn't belong — is critical to making the right investment.

Honeywell Forge is the enterprise IIoT platform from one of the world's largest industrial conglomerates. MachineCDN is a purpose-built manufacturing intelligence platform focused on rapid deployment and comprehensive factory visibility. Both serve industrial customers — but they serve them very differently. Here's what manufacturing engineers and plant managers need to know.

IoTFlows has positioned itself as an AI-powered industrial monitoring platform backed by Y Combinator, promising to reduce downtime through vibration and acoustic analysis. But does the reality match the pitch? After examining their platform capabilities, customer feedback, and competitive positioning, here's an honest assessment for manufacturing engineers evaluating IoTFlows in 2026.

If you're evaluating IoTFlows for your manufacturing operation, the first question is obvious: what does it actually cost? Unlike traditional software purchases where you pay a license fee and move on, IoTFlows combines proprietary hardware with cloud subscriptions — and that dual-cost model deserves careful examination before you commit.