Each year, contact injuries—those “struck-by” or “caught-between” machines, vehicles, or falling materials—cause thousands of serious incidents on the factory floor. In 2023, U.S. manufacturing alone saw $7.1 billion in direct losses linked to these accidents, with contact injuries ranking among the industry’s costliest and most disruptive safety challenges (Source: Liberty Mutual 2025 Workplace Safety Index; BLS CFOI 2023). The risk is everywhere: from machinery without proper guarding, to forklifts zipping through shared aisles, to tools left unsecured on overhead platforms.
But here’s the good news: most of these incidents are preventable. By pairing strong safety protocols with modern, AI-powered video intelligence, safety leaders can move from reacting after the fact to stopping accidents before they happen. This guide breaks down the true costs, root causes, and gives you a clear framework for moving from a reactive to a proactive safety model using the latest technology.
Why Contact Injuries Hurt Manufacturing Operations (and Budgets)
Contact injuries—where a worker is struck by moving equipment, falling objects, or caught between machinery—are among the top drivers of injury costs and operational headaches in manufacturing. In 2019, manufacturing recorded 3.3 non-fatal injuries per 100 employees, the highest of any industry, with 421,400 total injuries or illnesses reported (Source: ElectroIQ, 2025).
Beyond the numbers, these accidents often mean missed deadlines, overtime, and regulatory penalties. With the average OSHA penalty for serious violations exceeding $23,000 (Source: OSHA, 2025), the financial incentive for prevention is clear.
The Top 5 Causes of Struck-By or Caught-Between Accidents in Manufacturing—and How to Prevent Them
Understanding the “why” behind each incident is the first step. Here are the five leading causes, with practical prevention strategies and how AI video analytics can make your safety program smarter and faster.
1. Unprotected or Poorly Maintained Machinery
The Hazard:
A machine operator is clearing a jam on a conveyor. The moving parts are unguarded, and as the operator reaches in, their glove snags—a classic caught-in accident. These incidents account for thousands of manufacturing injuries each year, often resulting in finger or hand amputations.
Traditional Prevention:
Install and regularly inspect physical machine guards.
Use lockout/tagout (LOTO) procedures during maintenance.
Conduct manual checks to ensure guards are in place before operations.
How AI Amplifies Prevention:
AI-powered video analytics can monitor machinery zones in real time, flagging when safety guards are missing or when workers access hazardous areas without proper lockout/tagout. With instant alerts, safety teams can intervene before a near-miss becomes a serious injury—no more relying on post-incident reports or occasional spot checks.
2. Forklift and Vehicle Hazards
The Hazard:
During a shift change, a worker walks through an aisle as a forklift reverses with a pallet load. The operator’s view is partly blocked, and there’s no physical barrier separating pedestrians from traffic. Forklift near-misses and collisions are a top cause of struck-by injuries in manufacturing.
Traditional Prevention:
Mark pedestrian walkways and install physical barriers.
Require high-visibility vests and enforce right-of-way rules.
Hold regular operator and pedestrian safety training.
How AI Amplifies Prevention:
Video analytics can automatically detect when forklifts or other vehicles enter restricted (no-go) zones, or when pedestrians and forklifts come dangerously close. Real-time “forklift near-miss” alerts empower supervisors to respond immediately, refine traffic patterns, and reinforce safe behaviors where it matters most.
3. Inadequate Lockout/Tagout (LOTO) During Maintenance
The Hazard:
A maintenance tech starts cleaning a press, unaware that another employee re-energized the machine. The result: a caught-between incident. LOTO violations are among the most common root causes of serious injuries during equipment servicing.
Traditional Prevention:
Implement written lockout/tagout procedures and require LOTO certification.
Use manual checklists and permit systems for maintenance tasks.
Conduct periodic LOTO audits and retraining.
How AI Amplifies Prevention:
AI video systems can alert your team whenever someone enters a no-go zone during scheduled maintenance windows or accesses machinery without visible PPE or lockout devices. Reviewing flagged footage helps EHS leaders pinpoint policy gaps, verify LOTO compliance, and deliver targeted coaching to reduce repeat violations.
4. Unsafe Material Handling and Stacking
The Hazard:
A rigger is unstrapping a load of steel rods on a flatbed trailer. The rods shift unexpectedly and roll off, striking the worker. Improperly stacked materials, unsecured loads, and risky manual handling are behind a significant share of struck-by incidents.
Traditional Prevention:
Require load securing and regular inspection of stacked materials.
Train workers on proper lifting and rigging techniques.
Use signage and barriers to keep people out of hazardous areas during lifts.
How AI Amplifies Prevention:
Video analytics can detect when people enter dangerous stacking or rigging zones (“person enters no-go zone”), or when vehicles operate too close to unsecured loads. By surfacing these high-risk moments, safety teams can act quickly—stopping unsafe practices before they lead to an accident.
5. Missing or Improper Use of Personal Protective Equipment (PPE)
The Hazard:
A machinist operates a grinder without safety glasses. A fragment flies off, causing a serious eye injury. Inadequate PPE use is a recurring theme in OSHA investigations, especially in environments with flying debris or pinch points.
Traditional Prevention:
Post PPE requirement signage and provide necessary gear.
Conduct manual PPE spot checks and enforce discipline.
Include PPE training in onboarding and refreshers.
How AI Amplifies Prevention:
AI video analytics can automatically flag workers missing required PPE—such as gloves or safety glasses—when entering or working in hazardous zones. Immediate feedback gives supervisors a chance to intervene, while historic footage helps identify patterns or gaps in training.
Integrating a Modern AI Camera System: From NVR to AI Insights in Manufacturing
Upgrading your safety tech shouldn’t mean tearing out everything you have. Modern AI video platforms are built to work with your existing infrastructure—including standard POE (Power over Ethernet) cameras—so you can add advanced analytics without an expensive rip-and-replace.
Feature | Traditional NVR System | Modern AI Camera Platform |
|---|---|---|
Camera Compatibility | Often requires new cams | Works with existing POE cams |
Storage | On-prem hardware | Secure, cloud-native, scalable |
Maintenance | Frequent, on-site | Minimal, remote updates |
User Access | Limited seats | Unlimited users, one dashboard |
Video Review | Manual, slow | AI-powered, instant search |
Actionable Insights | Passive footage | Real-time safety alerts |
AI platforms bridge your legacy cameras to a secure, cloud-native dashboard, adding a smart analysis layer on top of your current video feeds. This means real-time alerts for everything from “forklift near-miss” events to “missing PPE,” so you can respond proactively—not just review footage after the fact.
Tips for Manufacturing Safety Teams:
Choose solutions that support existing safety goals and compliance with OSHA 29 CFR 1910.212 (machine guarding) and 1910.147 (LOTO).
Ensure compatibility with your current camera infrastructure—look for platforms that accept both modern and legacy feeds.
Prioritize systems that offer real-time insights and unlimited user access, so safety isn’t siloed.
Integrate new technology with your broader safety program—link incident reporting, training, and regular safety audits for a holistic approach.
Cut Contact Injuries—Strengthen Your Safety Culture
Every contact injury is a call to action. Today’s manufacturing leaders have more tools than ever to prevent struck-by and caught-between incidents—by combining strong protocols, hands-on training, and AI-driven video analytics that deliver instant, actionable insights.
Ready to see how AI video analytics can empower your safety team and help prevent the next serious incident? Book a safety consultation with Spot AI’s manufacturing safety experts for tailored, practical guidance that fits your operation’s unique needs. Book a safety consultation.
Frequently asked questions
What are the main causes of contact injuries in manufacturing?
The leading causes are unguarded or poorly maintained machinery, forklift and vehicle hazards, missing or inadequate lockout/tagout during maintenance, unsafe material handling and stacking, and missing or improper use of PPE. Each of these hazards is well-documented in manufacturing injury reports (Source: OSHA, 2025).
How can manufacturing organizations implement safety technology without disrupting operations?
Modern AI video platforms connect directly to your existing cameras, overlaying powerful analytics without interrupting production. These systems automate hazard detection and incident reporting, making safety teams more effective without changing workflows.
Are there compliance standards for preventing contact injuries in manufacturing?
Yes. OSHA 29 CFR 1910.212 requires machine guarding on hazardous moving parts, and 1910.147 mandates comprehensive lockout/tagout procedures for equipment servicing. Regular audits and safety training are essential for compliance (Source: OSHA, 2025).
What should I consider before adopting AI camera technology in my facility?
Start with a risk assessment to identify high-hazard zones and evaluate your current camera coverage. Involve safety, operations, and IT teams early. Pilot the system in a problem area, review results, and expand based on data-driven improvements.
How does AI video analytics help with incident investigations?
AI-powered platforms automatically flag near-misses and safety violations, making it easy to find relevant footage and understand root causes. This supports faster, more accurate investigations and helps teams update protocols to prevent future incidents.
How can safety technology help reduce stress for safety managers?
AI-driven analytics automate hazard detection and reporting, freeing safety managers from endless manual video review and paperwork. This means safety leaders can focus on proactive planning, training, and supporting their teams.
About the author
Joshua Foster
IT Systems Engineer, Spot AI
Joshua Foster is an IT Systems Engineer at Spot AI, where he focuses on designing and securing scalable enterprise networks, managing cloud-integrated infrastructure, and automating system workflows to enhance operational efficiency. He is passionate about cross-functional collaboration and takes pride in delivering robust technical solutions that empower both the Spot AI team and its customers.
