Predictive Maintenance

Predictive maintenance in Industry 4.0 uses big data and SAP Predictive Asset Insights to minimize maintenance costs and create new business opportunities.

5 Stages of Predictive Maintenance Connectivity

Connected production systems play a crucial role in unlocking the full potential of predictive maintenance programs. In order for machines to provide valuable insights and data that facilitate effective analysis, seamless communication is key, irrespective of the software solutions employed. The level of connectivity within a network is a clear indicator of the efficiency and efficacy of this innovative technology. As such, integration of production systems is increasingly becoming a vital component of modern industrial operations. With increased connectivity, businesses can better monitor equipment health, streamline maintenance schedules, and ultimately reduce downtime and costs. So, it is of utmost importance to embrace the power of connected production systems in order to reap the maximum benefits of predictive maintenance programs.

Offline

Machines in the plant operate independently, leading to separate data and missed synergy opportunities. Maintenance relies on experience without connected data.

Connected Assets

Machines are connected, but not collecting important data. Could cause problems ahead.

Asset monitoring

Real-time machine data is available for plant status and performance monitoring, but maintenance alerts must be scheduled and tracked separately.

Condition-based maintenance

Clear rules and guidelines make it easy to check the current condition of the machine, including when maintenance is needed based on usage, wear and tear, and other factors.

Fully data-driven maintenance

An all-in-one system alerts operators of service needs and automatically orders the correct spare parts, ensuring smooth and efficient maintenance.

Advantages of SAP Asset Insights for PM

Many companies use SAP solutions for predictive maintenance, especially SAP Predictive Asset Insights. This replaces SAP Predictive Maintenance and Service and offers many benefits to users.

Improved efficiency

By utilizing data-driven processes and implementing strategic maintenance plans that are automated, we can ensure timely provisioning of all necessary maintenance resources. This approach substantially decreases downtime and ultimately leads to an increase in overall efficiency.

Lower transport costs

Regular maintenance prevents surprises. Predictive maintenance reduces unplanned shutdowns, lowering freight costs and avoiding special deliveries due to delays.

Lower production costs

Machinery that is properly maintained and serviced before thresholds are exceeded, is the key to achieving a consistently reliable and efficient production output. This helps to minimize losses, maximize productivity and ultimately optimizes overall production costs for the long haul.

Greater cost efficiency

Reduce maintenance costs and ensure optimal performance with SAP Asset Insights. By leveraging data, choose and execute maintenance at the most opportune time for your organization's needs.

Improved supply chain

Predictive maintenance is absolutely critical for logistics-oriented just-in-time production considering that it plays a key role in optimizing equipment uptime, which is essential for achieving operational efficiencies and cost savings.

Just-in-time maintenance

If you know ahead of time which part requires replacement or where a specific service engineer is needed, you can plan and prepare accordingly for a smoother process.

Use cases for pM

The advantages of predictive maintenance are truly remarkable and benefit a wide range of manufacturing and production industries in different disciplines. With its cutting-edge technologies and innovative approaches, predictive maintenance has revolutionized the way businesses function in the modern world. Here are three potential areas where predictive maintenance can bring about a significant change:

Bulk Production

Our esteemed customer forged a solid partnership with Zircoo to effectively implement SAP Predictive Asset Insights, thereby optimizing maintenance stoppages to ensure seamless and streamlined production processes. Through comprehensive analysis of historical data, our team unveiled groundbreaking insights that led to a drastic reduction in disruptions.

New Busiess Models

In conjunction with connected machines, companies can use predictive maintenance and SAP as the basis for new and innovative business models. By shifting focus to providing access to operating hours as part of an Uptime as a Service approach, rather than simply selling machines, businesses can benefit from secure, constant revenue streams. Thanks to the solid foundations provided by predictive maintenance, companies can ensure their services are always at optimal levels, even in ever-changing markets.

Zircoo: Your partner for predictive maintenance – not just with SAP

To fully harness the advantages, it’s essential to grasp and deploy the requisite technologies effectively.

Zircoo, as a seasoned IT services provider, boasts a track record of crafting and executing numerous projects across diverse industries. Our clients opt to collaborate with us for various reasons, but chiefly for our profound comprehension of production system processes, nuances, and prerequisites. We understand the motivations driving companies aiming to leverage the potential of predictive maintenance to the fullest. As a longstanding SAP partner, we ensure seamless integration of SAP Predictive Asset Insights into existing SAP ecosystems.

Moreover, our demonstrated proficiency in cloud technologies empowers us to adeptly devise and implement bespoke architectures and provisioning models. The cloud serves as the cornerstone for our Zircoo IIoT Portal, offering companies tailored solutions and applications that offer insights into future machine performance and maintenance schedules. Whether it’s process consulting, IT, OT, or cloud services, Zircoo delivers comprehensive support under one roof.

FAQ: Predictive Maintenance

Predictive Maintenance: An Overview

Predictive maintenance is key to identifying potential servicing and maintenance needs early on, using data from the machines to predict requirements. AI and ML algorithms can be used to identify patterns and prevent issues before they occur, ultimately making production processes more efficient, increasing productivity, and reducing unscheduled downtime.

Predictive vs Preventive Maintenance: How Are They Different?

Predictive maintenance uses data to forecast machine failure and optimize spare parts. It’s more cost-effective than preventive maintenance, which replaces parts at set intervals regardless of their condition.