Operating in silos stifles an organization in the long run, so much so that Harvard Business Review, in one of the articles, called it “#1 Innovation Killer in the Company.” Read this blog to uncover how you can break silos in manufacturing across departments with technology in manufacturing and improve efficiency radically. 

Maintenance Vs. Operations

As manufacturing companies chase to minimize the equipment downtime, they’re often caught in an ‘Us vs. them’ situation between maintenance and operation teams. 

According to Plant Services, here’s the most common scenario observed – the operation team blames the maintenance team for downtime events. They think the maintenance team takes too long to fix the equipment and isn’t proactive in informing the operations teams. 

The maintenance team, on the other hand, feels the operations team isn’t trained well enough to handle equipment and is also laid back in notifying the maintenance team about the downtime occurrence. As a result, there’s a clear communication gap that creates an information silo.

If anything, such silos further worsen the downtime consequences and often waste hundreds of thousands of dollars (as reported by Plant Services).  It is no wonder then that every manufacturing leader wishes to break silos in manufacturing plants across operations & maintenance teams.

Machine Downtime Vs. Production Downtime

Organizations need to integrate maintenance teams with operations and production to enhance uptime rather than consider them as standalone service teams. This shifts the approach from reactive to proactive.

There has to be a clear line between production downtime vs. machine downtime. Any material shortage that leads to schedule disruption is a classic case of production downtime and the primary responsibility of production teams. Any downtime attributed to equipment (and not materials) is a machine downtime – which would be the maintenance team’s responsibility. 

The operation supervisor must keep track of production downtime, and the maintenance supervisor must keep track of machine downtime. The data collection process intends not to pass the buck but to analyze the data so that future downtime can be averted or better anticipated. The key is to get to the root cause of the problem and figure out ways to solve the problem rather than a blame game –  and here’s where technology can help.

Technology to Break Silos in Manufacturing

Data collection need not be carried out manually; you can attach sensors to the machines to make it automatic. These sensors would collect and feed the data to the systems periodically, but that’s a fundamental & commonplace technology implementation.  It is how frequently & effectively you can monitor the data collected that can make the system excel. It is here that advanced technologies like Artificial Intelligence (AI) in manufacturing can help companies break the silos in manufacturing plants and drive operational resilience. It is only then that predictive maintenance can be implemented in the truest sense.

Leveraging technologies to improve inter-departmental communication isn’t a new concept. Many other industries are doing it too. 

According to MIT Sloan Management Review, US-based company People.ai  launched a platform that introduces communication between marketing and sales teams regarding pipelines, lead follow-ups, and campaign performance. The platform has improved collaboration and visibility – which results in better target achievement.

Other companies like UPS, the Atlanta-based shipping company, and Becton, Dickinson and Co., a large medical tech company, use technology to reduce silo-driven problems in their companies and drive efficiency.

How an Industrial AI solution can break the silos in manufacturing

A custom-built AI application for plant operations like UptimeAI can help companies detect the exact cause of machine downtime. It allows companies to cut down unnecessary noise and pay attention to only the relevant alarms with the underlying causes.

The Virtual AI Plant Expert doesn’t just raise alarms pointing to an oncoming issue but also offers critical insights into plant health. This unlocks predictive maintenance at a plant level to allow asset managers to plan for maintenance activities, asset failures, replacements, and repairs. 

Precise insights empower the plant manager to take the right action rather than speculate and get involved in the maintenance vs. operations debate. It does the opposite by not leaving room for conflict as the data is readily available & understandable to everyone. The clear visibility enables plant managers to break silos in manufacturing & promotes collaboration between the teams. There are numerous benefits to this including enhanced productivity, lower downtime, and a far more significant improvement in asset performance, reliability, & availability.

Are you looking forward to running plant operations efficiently with minimal downtime-attributed losses? Reach out to our team of experts at info@uptimeai.com.