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The 5-Minute Guide to Reducing Downtime in Manufacturing with IOT

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Digital Transformation

The 5-Minute Guide to Reducing Downtime in Manufacturing with IOT

How to Reduce Unplanned Downtime in Manufacturing 

  • Eight in 10 companies recognise that digital tools can eliminate unplanned downtime, and zero unplanned downtime is now the number one priority for 72% of organisations surveyed. How downtime can be minimised is the core question being considered in every forum.
  • 60% of businesses confirm that digital transformation is a high board-level priority, and 56% report the same for innovation.
  • Proactive maintenance is a maintenance strategy that corrects the source of underlying equipment conditions. The goal of proactive maintenance is to reduce unplanned downtime, equipment failure, and risks associated with operating faulty equipment. 
  • Empowering employees and adopting a proactive, disciplined mindset is just as important as preventative maintenance and smarter software systems and technologies.

With the rise of Internet of Things and big data, companies now have the liberty to leverage machine data to limit the costs and impacts of downtime, irrespective of whether it is planned or unplanned. This protocol of crisis management is, in a nutshell, referred to as predictive maintenance.

Here are some tips for reducing machine downtime:

  • Undertake a risk audit. Despite advancements in control systems, a great number of manufacturers still work with equipment that’s 15 to 20 years old – ageing systems that are no longer supported by manufacturers. Parts often become unavailable, or are made out of the country, and it take weeks to deliver. Knowing your support network and equipment availability can influence the difference between a few hours or a few months in a downtime event.
  • Calculate the cost of machine downtime. Downtime in manufacturing includes losses in staff productivity, in production of actual goods, and in the number of man-hours devoted to rescheduling in addition to the unexpected costs of repairing equipment and time spent satisfying customers. When converted into a calculated cost figure and paired with a preventive and proactive mindset, this can go many miles towards saving and focusing on reducing machine downtime.
  • Harness data and reporting systems. Different operational and IT systems can be integrated to provide a plant-wide view. This helps manufacturers pinpoint the exact moment a machine goes down, allowing them to cross-check against other activities in the plant and find a correlation.
  • Install low-cost sensors. Sensors can detect inputs such as vibrations, temperature, heat and light – conditions that are likely to cause equipment damage or failures. They then send the data back to a central point to alert production managers if anything is unusual. This prompts operators to change the conditions and avoid equipment damage, thereby helping arrest downtime before it can happen.
  • Adopt a proactive mindset. The thought and culture perspective will play a large part in determining if preventative maintenance, staff training and other measures can be successful in reducing downtime. This will also help in training and empowering employees who have the potential to curb machinery downtime and prevent future machinery downtime events. Empower operators to diagnose and problem-solve their machines and remind them how their actions can positively impact downtime. 

Enable Manufacturing Companies with Industry 4.0 Solutions

How will IoT data help you determine downtime types and priorities?

What is the Internet of Things, you ask?

IoT refers to everyday devices that possess network connectivity, enabling them to send and receive data. It is a system of interrelated computing devices, mechanical and digital machines, objects and people that have unique identifiers (UIDs) and the ability to transfer data over a network without the need of human-to-human or human-to-computer interaction.

Manufacturing is evolving for the better and fast. IoT offers product creators a deeper insight into their uses. Once in the hands of customers, the data provided by any connected device can be used to streamline processes and remove inefficiencies from the engineering process.

An industrial IoT application coupled with a strong predictive maintenance system can improve overall equipment effectiveness by at least 10 times.

This is how the system works:

IoT devices (with sensors) are fixed on the machines, and its real-time downtime and performance under different conditions are captured before being pushed to mobile data and to cloud IoT platforms.

The data is then fed into an AI- and ML-based predictive maintenance system that have the ability to predict unplanned machine downtimes. The entire system provides a massive volume of real-time data that helps in improving the OEE at the work centre.

To read more: Guide to Calculating & Improving OEE

Predictive Maintenance

Predictive maintenance refers to conducting maintenance runs in a bid to keep predicted problems at bay. It can be seen as a proactive method of foreseeing maintenance requirements on the factory floor and addressing such issues immediately rather than sticking to the traditional condition-based maintenance, which involves carrying out maintenance following a fixed schedule or only to combat a issue that has suddenly come up. Predictive maintenance involves analyzing operational data from machines, which provide a host of indicative patterns and insights. Operators then utilize these patterns to predict a unit’s maintenance schedule within the system. 

At Hakuna Matata, a leading digital transformation service, we look at how digital transformation can help companies like yours leverage the potential of digital technology to the fullest. We adopt the best in design thinking, domain and client expertise to service you. Discover how to minimise downtime and how our IoT services and solutions can save you time and money right here

Did you Know that 46% of unplanned downtime is caused by hardware failure or malfunction and 40% due to software malfunction? Or that an outage lasting for an average of approximately four hours costs over 3 million dollars in financial losses? Needless to say, downtime brings about loss of customer trust and negatively impacts productivity and key performance indicators (KPIs). For manufacturing, managing machinery downtime is the need of the hour! Let’s dive right in and see how one can minimise machine downtime with the help of the latest know-how and business-friendly IoT services. 

What are the Types of Machinery Downtime?

Businesses operating in the manufacturing domain know how important it is to reduce downtime. Any break in the production line due to a failure in even the smallest of components can result in significant financial loss. 

First, let’s understand the different types of downtime in manufacturing:

  • Planned downtime is a specifically scheduled downtime meant to address equipment performance, hardware/software upgrades, facility maintenance, tool breaks, inspections, and to perform other necessary upkeep. Since planned downtime is anticipated, it is also controlled in terms of time and money invested as well as productivity and labour losses.
  • Unplanned downtime is any unforeseen event that reduces return on investment by causing disruptions in quality, cost and cycle time. It usually refers to an equipment event, such as poor maintenance or hardware/software errors, operator error/performance and/or slow changeovers. Unplanned downtime contributes to lost time and revenue..

Common categories of unplanned downtime include excessive tool changeover, excessive job changeover, lack of operator, and unplanned machinery maintenance. Unplanned downtime not only seriously impacts production but also subjects workers to safety risks from faulty equipment.  Investing time and resources in proactive maintenance also significantly extends the life of an asset.

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