How Data Analytics Can Keep Your Manufacturing Employees Safe
How Data Analytics Can Keep Your Manufacturing Employees Safe

While overall workplace injuries and illnesses are trending downwards—373.3k in 2020 vs 421.4k in 2019—employee safety is always top of mind for the manufacturing industry. There were 340 work-related fatalities in 2020 alone. Data analytics can help to lower those numbers. 

Employee health and safety is important to both the employee and the employer. Beyond labor interruptions and the cost to the company’s bottom line, your employees should feel safe and protected while working in your facilities. 

It is more than just your duty to follow OSHA regulations, it is a responsibility you have to all employees to make sure they are working in a safe environment. Manufacturing comes with a significant increase in safety issues. The machines utilized in plants and factories cause any number of potential issues from crushed fingers and amputations to chemical exposure resulting in burns and blindness. In fact, contact with an object or equipment was one of the most expensive causes of workplace injuries totaling over $7 billion across all industries in 2021. 

Manufacturing employees are at risk of issues like overexertion, repetitive stress injuries, falling objects, electrical incidents, vehicle accidents, and machine-related injuries that are common in this space. 

Manufacturing Safety Tips

It is always important to follow the OSHA guidelines for the manufacturing industry and cultivate a safety culture that keeps employees and employers informed and safe. 

Frequent audits and inspections are recommended in addition to regular safety meetings to go over guidelines and procedures. Slips and trips are the second most prevalent cause of nonfatal work-related injuries so keep walkways, stairwells, work areas, and emergency exits clear. 

And, employ data analytics to automate safety precautions and make for an overall safer environment for workers. 

Data Analytics Can Contribute To A Safer Environment

Data Analytics Can Contribute To A Safer Environment

The Industrial Internet of Things (IIoT) is modernizing factory infrastructure and bringing in a new era of Smart Factories. Data analytics can do more than streamline operations and increase profitability; predictive analytics allow for the accurate forecasting of everything from downtime to labor needs. 

Data analytics contribute to the overall safety of the environment in three main ways:

1. Data Monitoring and Sensor Connection

Smart Factories utilize AI and machine learning softwares to collect aggregate data from across facilities and ecosystems and provide critical insights. These software solutions are able to integrate sensors and collect millions of data points from the factory floor—even across multiple facilities. 

Your teams will have a centralized view of machine-to-machine (M2M) data, like fault codes, time stamps, and system alerts, correlated across machines providing visibility of equipment failures and safety-related shutdowns. 

Operators and managers are able to rely on this M2M data to create a safer environment for employees. With a deeper understanding of the location and frequency of unsafe working conditions, manufacturers can reduce employee exposure to potentially dangerous elements and equipment with risk. 

2. Predictive Analytics

Preventative maintenance is still the most common approach to dealing with machine downtime and repair schedules. Reliance on the mean time between failure (MTBF) can lead to more frequent downtime and higher maintenance costs. 

Manufacturers who have switched to predictive maintenance have less downtime, lower costs, and fewer equipment emergencies. Predictive analytics in manufacturing allow for the monitoring of performance and asset health with real-time operational performance data. By combining real-time analytics with historical data from across the factory floor, you’ll be able to identify performance degradation and predict potential issues before they occur. 

Fewer equipment emergencies and a repair schedule based on the actual condition of the machine will reduce the number of potentially unsafe conditions that lead to work-related injuries. 

3. Capacity Management and Shift Reports

Machine learning capacity planning eliminates the need for labor-intensive manual processes that often lead to mistakes. With software solutions, like Sightline EDM®, the data collection process is streamlined and analysis is conducted in real-time. You will be able to anticipate trends, allocate resources and personnel appropriately, and forecast infrastructure requirements well in advance. 

Real-Time Data Analytics For Real-Time Safety Precautions

Real-Time Data Analytics For Real-Time Safety Precautions

Sightline EDM® provides the OT intelligence and enterprise data insights manufacturers need to ensure they maintain safe environments for their employees. Integrate ecosystems and streamline processes across the factory floor in one unified, centralized dashboard for the most holistic view of your operations. 

Sightline predicts the future, intelligently. With advanced data analytics, real-time monitoring, and 24/7 alerts, your employees can feel secure in their work environment. 

See Sightline in motion or book a conversation with an EDM® expert to see how you can harness the power of AI and advanced analytics to contribute to a safer manufacturing environment. 

FAQ’s

What are the 3 ways Data analytics contribute to the overall safety of the environment?

1.. Data Monitoring and Sensor Connection
2. Predictive Analytics

3. Capacity Management and Shift Reports

What is recommended in addition to regular safety meetings to go over guidelines and procedures?

Frequent audits and inspections

What is important to follow to keep employees and employers informed and safe?

The OSHA guidelines for the manufacturing industry

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