Safety on the shop floor is a key area that manufacturers need to monitor, from a humanitarian as well as a government regulatory compliance standpoint. Studies show improvement in areas like productivity and quality, as workers are more motivated in a safe environment.
According to the ILO, every day, people die because of occupational accidents and work-related diseases – more than 2.78 million deaths per year. Additionally, there are some 374 million non-fatal work-related injuries each year, resulting in more than 4 days of absence from work. The human cost of this daily adversity is vast and the economic burden of poor occupational safety and health practices is estimated at 3.94 per cent of global Gross Domestic Product each year.
Industry 4.o or the Fourth Industry Revolution has a lot to offer to the Manufacturing Industry and there are benefits already visible in areas of Productivity, Costs and Quality.
What about Safety?
There is a lot of focus on using the latest digital technologies like IoT, AR/VR, Digital Twin, providing significant business benefit to the company. But what about safety? Is the Shop floor worker- the key stakeholder in manufacturing - missing the boat?
One of the fundamental principles of Japanese Manufacturing & Shop floor regulations is that safety is the most important and basic pillar of the shop floor.
Normally shop floors measure safety with the help of KPIs such as number of accidents on the shop floor. This is a flawed measurement practice, as it is not only a post facto number but also fails miserably to capture the details of safety aspects in a quantitative way. Enormous efforts and strong commitment from upper management is required to meet the objective of zero accidents. Industry 4.0 provides an excellent opportunity to significantly improve shop floor safety.
Another fundamental principle of safety is that any major accident does not happen by chance! There are minor incidents and ‘near-miss’ cases ignored over a period which lead to a major accident.
Is ensuring Shop Floor Safety easy?
One of the key challenges in managing the safety of the shop floor is that its environment is very dynamic; material movement, machines, robots, forklifts, material handling, handling of hazardous material and workers sharing the space with machines. Further, any modification in production volume, layout or manpower changes the focus to more tangible targets like productivity and quality, while safety is assumed to be taken care of, in reality, it is not!
Even a single mistake can lead to an accident or provide threat to safety.
There are various comprehensive safety guidelines available but it is difficult to convert the theoretical concepts to a practical solution executable in such a dynamic environment of the shop floor. One such example is the Japanese safety principle of KYT (Kiken Yochi Training). This comprises observing each and every aspect of the shop floor in real time, like movement of workers, their hand position & angle of bend, rack stability (Height to Breadth Ratio), crossing of man and material on the shop floor etc. Ironically, it often happens that all these factors are inspected post a safety incident. While KYT tries to understand the prevailing conditions of the shop floor by making these observations and finding out hidden hazards based on risks associated with each activity, it provides useful insights on how to reduce these risks before they lead to an accident. Practically, it is very difficult to make such tedious observations and conclusions manually. (I have tried to do this with pen and paper and concluded that full justice to the work cannot be done manually). This is where advanced technologies available from Industry 4.0 can provide the means to do such kind of analysis and convert theoretical concepts into technology solutions.
Industry 4.0 & Shop Floor Safety
Industry 4.0 provides the opportunity to convert the ideal conditions mentioned in safety manuals to executable realities on the shop floor by leveraging three innovative technologies IIoT (Industrial Internet of Things), ML (Machine Learning) and Big Data & Advanced Analytics.
Combining these technologies, there can be a systematic tool to observe and collect the various shop floor data and then make a continuous, meaningful conclusion to enhance safety.
IIoT can be leveraged to capture all required data from the shop floor in real time with the help of sensors, cameras, IMU (Inertial measurement unit). The data captured can be used to determine the safety level at worker, workstation, assembly lines, and combining them to overall shop floor level. Based on this assessment, the system will take appropriate countermeasures or alert the supervisor. It will leverage principles of Machine Learning (ML), which will work without human intervention and continuously learn to enhance safety on the shop floor. Also, the model will have a dedicated module to predict the hazard by leveraging Big Data and Advanced Analytics and hence provides the ability to predict a hazard and perform a ‘What -If’ scenario analysis.
Safety on the shop floor is a real concern that needs to be addressed with the best possible means. Industry 4.0 has tremendous potential to make a significant reduction in the number of work-related accidents. Technology, after all, is for humans. Not the other way round.
Domain Lead Global Automotive Domain Practice at Wipro Ltd
Ashish Shrivastava is Domain Lead for ‘Design to Ship’ processes in the Global Automotive Domain Practice at Wipro Ltd. Ashish has over 19 years of business experience spanning multiple roles in Manufacturing, Logistics & SCM. Before joining Wipro, Ashish worked with Infosys where he gathered hands-on experience in multiple business transformation, ERP Implementations & IT Consulting projects for global clients. He also has rich domain experience at Maruti Udyog Ltd. (Suzuki Motors Corporation) Having worked closely with clients in multiple stints in 13+ countries, Ashish focuses on leveraging this experience with innovative digital technologies such as Industrial IoT, Cloud, Blockchain and Artificial Intelligence/Machine Learning to help customers realize business outcomes. Ashish holds a degree in Mechanical Engineering and an MBA.