What You’ll Find in this Case Study:
- Highlights of the Case Study
- Game-Changing Solutions for the Food and Beverage Industry
- Food Predictive Analytics Challenges of the Manufacturer
- Food Predictive Analytics Solutions for the Food and Beverage Industry
- Impact Analysis of Quantzig’s Food Predictive Analytics Solutions
- Key Outcomes of Food Predictive Analytics in the Industry
- A Broad Perspective on the Role of Food Predictive Analytics Solutions in the F&B Industry
- Key Takeaways
Highlights of the Case Study
|Client||A major Canadian multinational food and beverage manufacturer collaborated with Quantzig to increase the uptime and reliability of its production machines.|
|Business Challenge||The client wanted Quantzig to help develop agile methods to deliver high-quality products, adhere to delivery schedules, and reduce maintenance costs.|
|Impact||Quantzig leveraged its cutting-edge big data analytics solution to develop predictive maintenance schedules to reduce downtime. This helped the client to optimize the production process and improve operating efficiency.|
Game-Changing Solutions for the Food and Beverage Industry
The food and beverage industry had already adopted several Industrial Internet of Things (IIoT) technologies to boost uptime before the COVID-19 pandemic even started. Professionals experimented with various connected sensors, tools, software, and equipment to conduct remote condition monitoring, maintenance, and reliability. There is a resurgence of interest in new technology to help streamline operations because of supply chain problems, stringent regulations, and cost-cutting initiatives. The adoption of technology has accelerated over the last two years.
The idea of predictive maintenance offers a variety of ways to automate processes and provide services for remote monitoring. Companies in the food and beverage industries use several cutting-edge software programs to enable predictive maintenance. A data historian enables basic time series and historical data analysis to identify the root causes of previous failures, empowering operators to take preventative action to address these problems. Quantzig offers big data analytics solutions to help detect equipment failure and boost productivity.
Food Predictive Analytics Challenges of the Manufacturer
A major Canadian multinational food and beverage manufacturer collaborated with Quantzig to increase the uptime and reliability of its production machines. The client wanted our assistance in developing agile methods to deliver high-quality products, maintain delivery schedules, enhance safety, and reduce maintenance costs. The client approached Quantzig for its AI & predictive analytics solutions in food industry to optimize resource utilization and improve efficiency. Our client was seeking to resolve the following issues that were hampering its operations:
- Inconsistent product quality
- Unscheduled downtime
- Unscheduled equipment maintenance and unplanned repairs
- Missed production timelines
- Ensuring compliance with regulatory standards
Quantzig’s predictive analytics is applied to all types of data sets, including unstructured data and time series, to identify future faults in machinery. The solution is integrated with existing systems to help companies better understand equipment behavior and coordinate maintenance events seamlessly.
Food Predictive Analytics Solutions for the Food and Beverage Industry
Quantzig helped the client by developing a predictive analytics solution to reduce downtime. Machine learning (ML) technologies and data models helped identify patterns in machine failure occurrence, which could be used for prescriptive maintenance. Quantzig’s artificial intelligence solution optimized the entire production process and increased uptime.
Moreover, real-time operational intelligence (RtOI) and predictive analytics solutions enabled the client to stay on top of operations in all its factories. This enabled insights into potential production roadblocks before the impact. Our predictive analysis system implemented the following to drive production efficiency:
- Automatic tracking of production
- Real-time monitoring
- Shortened response time
- Tracked machine performance
- Preventative maintenance
- Asset optimization
Impact Analysis of Quantzig’s Food Predictive Analytics Solutions
Quantzig’s predictive analytics solutions helped the client to unlock the following benefits to improve the lifespan of machinery by implementing predictive maintenance protocols. This also helped bring about a reduction in downtime and thus enabled the client to meet production schedules. It also helped to reduce maintenance costs and minimize raw material wastage and supply chain disruptions arising from unscheduled downtime.
Using Quantzig’s solution, the client could optimize the production process, improve operating efficiency, and implement technologies to reduce downtime and changeover times. This led to long-term benefits such as increased revenue and better customer relationships.
Key Outcomes of Food Predictive Analytics in the Industry
In a food manufacturing setup, unplanned downtime caused by breakdowns can incur staggering financial losses from spoilage of new ingredients. It can also lead to losses resulting from unmet production targets, which can lead to losing customers to the competition. Hence, there is an increased demand from many food and beverage companies to increase uptime by embracing predictive maintenance using IoT-enabled parts or bright parts to repair and replace a part before it fails proactively.
In collaboration with Quantzig, the F&B client could implement systems and protocols that enable predictive maintenance, resulting in increased uptime and improved production efficiency.
A Broad Perspective on the Role of Food Predictive Analytics Solutions in the F&B Industry
Although a cloud-based solution is the end-all-be-all of streamlined and adequate food and beverage manufacturing, it still needs to be monitored for general operation, maintenance, and administrative specifics. A few companies guarantee 99.7% uptime and accessibility in the food and beverage industry; this guarantee only relates to the cloud infrastructure, not the applications or data.
Imbalances or errors in configuration, resource allocation, and databases can cause an ERP solution to malfunction, which is where uptime monitoring excels. Controlling, observing, and improving system operations to prevent downtime is known as uptime monitoring.
Quantzig’s Predictive Maintenance Solutions yielded the following benefits for the F&B manufacturer:
- Improved machine lifespan
- Protected against outage and abnormal supply conditions
- Reduction in downtime
- Increased production
- Minimized maintenance costs
- Improved relationship with customers