Making the Most of What You Got
How the digital revolution can help maximize your assets and lower costs
By Folkert Haag, Global Lead, Building Materials and Building Products, SAP
$ 5 Million a Day
The cost of having an excavator go down in the field. (VentureBeat.com)
$1.8 Million a Day
The cost of losing a haul truck. (VentureBeat.com)
$.1 – 1 Million an Hour
The cost of unscheduled mill machine downtime. (SAP.com)
Cement manufacturing is one of the most capital intensive industries in the world. Cement plant operations require extensive investment in high-priced assets such as kilns, transportation fleets or mining equipment. Assets , including kilns that must run 24 hours a day, 365 days a year, need to operate at or near capacity at all times to distribute high fixed costs and debt. As the statistics above show, every minute an asset is down can have significant impact on a company’s bottom-line profitability. For this reason, maintaining asset uptime has always been important, yet in today’s ultra-competitive, global environment, efficiency is king. To improve operational efficiency and keep costs low, visionary companies are using new technology innovations to gain real-time insights into their daily operations.
Although the industry as a whole traditionally has been slow to invest in new technologies, a major industry survey by Mining Journal found that 10 of the world’s top mining companies see big data as one of the game-changing technologies poised to transform the industry in the next five to 10 years. Yet, as in any mining or production operation, the key to seeing quantifiable benefits lies in uncovering the most valuable data, determining where it can be most impactful, and then using it to make better decisions.
Real-Time Asset Visibility
Leveraging technology to improve asset management and reduce costs begins with gathering data in real-time. With embedded sensors in virtually every asset, companies now can achieve a real-time view and understanding of all their machinery. Organizations can gather information from every piece of equipment and every worker such as up-to-date measurements of gas and oil pressure, temperature, and schedules. Additionally, data such as fuel consumption per hour, tons per hour, or tons per shift is gathered to create KPIs on individual quarry vehicles, which can be helpful particularly for cement companies with equipment in remote locations. Once the data is collected, it can be stored and analyzed using high-speed, in-memory processing platforms, which are often accessed through cloud-based applications. In this way, maintenance decisions are no longer predicated on guesswork or historical data, but rather based on the actual condition of the asset. A few examples of taking action based on transmitted data to save money include:
- Condition-Based Maintenance – Making maintenance decisions based on the actual condition of the assets is much more efficient that working according to a fixed scheduled based on historical data. By monitoring real-time sensor data, cement companies can be alerted immediately when a machine or part may soon be in need of repair or replacement, such as when the steel balls inside a grinder are wearing out. Consequently, service technicians can be dispatched to resolve the issue before it results in downtime and at a time when it will cause the least disruption to operations. What’s more, service managers can detect worn equipment, such as a drill bit becoming dull, and automatically order a replacement to avoid additional downtime due to inventory issues.
- Fleet Optimization – Some cement companies are using data for precision tracking of their transportation fleets. Because limestone can not be transported long distances, cement plants typically are located near quarries. This means that products must travel long distances from the manufacturing facility to the end-users, making transportation efficiency a critical component in reducing operational costs. Data transmitted from smart vehicles helps avoid collisions by alerting control centers or following trucks when a vehicle is slowing down. Sensors are also being used to provide data on the weight of a truck, how it was loaded, its condition, its fuel usage, and its tire pressure. In this way, one mining company discovered that its truckloads were leaving the mine at 85% capacity, resulting in extra trips, more gas and driving time, and additional maintenance costs. Using the data as a guide, the company changed it practices to load vehicles as close to 100% as possible, resulting in significant savings and a reduction in the time needed to bring targeted quantities of resources to market.
- Automation – Technology is being used for work in remote locations such as drones inspecting long, linear assets like conveyor belts or track. Also, some cement companies are putting sensors in cement. When the cement begins to dry in transit, the sensors automatically alert operators who then re-route the cement to the job site. In this way, data is being used to preserve product integrity and avoid costs related to product loss.
- Procurement – Procurement can be especially costly for cement companies because it involves coordinating services for operations in remote places, across the globe. Cement companies often deal with many different suppliers and many different parts. Using real-time data, companies have an accurate account of current and future needs as well as inventory status, which helps avoid part shortages and unplanned downtime.
Cementing the Data for Asset Insights
Now more than ever with the convergence of smart devices, advanced connectivity, and platforms to manage the collaboration, companies can “mine” not only limestone, chalk and clay – but data as well. By taking real-time data and adding additional internal or external data, it is possible for companies to identify trends and make better predictions, which improve overall business performance.
Predictive maintenance is one application of taking money-saving action based on advanced data analysis. Predictive maintenance is performed by monitoring and gathering data; adding historical data, forward forecasts, and advanced algorithms; then predicting when assets are likely to break or need service so that proactive maintenance can be performed for a fraction of the cost. As an example, companies can predict maintenance needs on excavating machines located in different areas of a mine based on environmental factors that can cause variations in wear rates. Additionally, all maintenance on a kiln or oven can be coordinated so that it only needs to be brought down once a year at a time when it will have the least impact on output volumes.
In addition to savings resulting from fewer unplanned outages, cement companies can lower operational costs with more efficient coordination of maintenance. This is important for companies with remote locations because they are able to synchronize the arrival of maintenance technical and the correct parts in order to achieve higher first call resolutions. This is one reason why companies are forecasted to grow their investments in M2M technology to $85.96 billion in total annual revenues by 2017 (MarketsandMarkets.com).
Benchmarking is another key tool for maximizing asset performance, as companies can compare the performance of any given to industry standards in real-time. Benchmarking allows a company to compare its own results to partners, competitors, or other relevant third-parties, to understand whether operations are inefficient, on par with others, or performing above expectations. This insight helps decision makers make instant adjustments and continuous improvements to maximize performance. For instance, companies that have benchmarked against open data provided by the US government in its Energy Star Performance tool, which provides benchmarking data on energy usage across industries, have reduced asset consumption of electricity to achieved savings of 9 to 18% in electricity costs.
Asset intelligence network
The third evolution of big data for asset management will be realized when companies begin exchanging data with supply chain partners and customers to create an intelligent asset network. In this scenario, repair and maintenance information is shared with all parties to analyze problems and develop innovative solutions. What if the same mill part fails at different sites? Or what if a kiln operating at a certain temperature has a longer lifecycle? With this type of information exchange, companies can dig into the performance of their assets, perform root cause analysis and develop more effective maintenance strategies. Collaboration throughout the asset network also can help streamline remote maintenance procedures. Using videoconferencing, as well as 3D visualization tools, groups of experts including those from the manufacturer, supplier, and customer can work together to solve problems.
A report by McKinsey & Company states that mining, metals, and similar industries are using advanced analytics to find improvements in their production areas and solve previously unsolvable or hidden problems such as “bottlenecks, operational rigidities, and areas of excessive variability.” As a result, they are realizing an additional 2-3 percentage points of margin. Yet, companies in natural resource industries say they spend just 1% on information technology compared with 5-7% for most industries. This underinvestment means that cement and related companies collect data but have a limited understanding of how it can be used to better management existing assets.
With the technology available for collecting, analyzing and applying data analytics, cement companies should not be in the dark about their assets. Instead, there is a tremendous opportunity to make the most of these investments and save money through more efficient maintenance and collaboration. The data already exists. Now is the time to take control of the information and proactively manage assets on a schedule and a budget that improves customer satisfaction and increases profitability.
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