There is no question that disruptions in any business cause immediate outlay and potentially have a longer-term impact from lost business.
Thankfully, AI solutions have found ways to circumvent or minimize equipment failure-related disruptions by monitoring and analyzing operating conditions to essentially predict them.
Saving Thousands in Equipment Damage
AI can help customers minimize the costly disruptions caused by malfunctioning machinery. Predictive and preventative maintenance technology uses AI data from IoT sensors, PLC networks, and log files to track equipment’s health.
Unlike manual checks, this technology monitors equipment status 24/7. Users and customers get automatic alerts when the technology senses the need for maintenance, helping users prevent costly equipment failures and business disruptions.
Field service AI systems
Combined with real-time data analysis, AI can help users complete remote diagnostics
Field service AI systems can also monitor the mean time before failure (MTBF) and the mean time to repair (MTTR) allowing users to make data-driven decisions about corrective actions. When an imminent issue arises, the user will get instant critical fault alerts.
Combined with real-time data analysis, AI can help users complete remote diagnostics and dispatch a repair technician. This technology will effectively minimize equipment downtime preventing costly and presentable disruptions.
Eliminating Workflow Bottlenecks
What if the user could detect the exact source of the customer’s production disruptions? While this may be impossible for most field service providers, it is well within the capacity of AI technology.
AI technology can create a “digital twin” of the customer’s equipment and operations. This technology gathers data and digitally recreates simulations of how equipment and operations should function. AI technology then compares this information to the data produced in the real environment.
digital twin comparison
The digital twin comparison can pinpoint the cause of bottlenecks in a production workflow. For example, it may detect that one machine is working slower than the others, or perhaps a certain shift of personnel is delaying production.
Once the sources of these issues are identified, the user and the customer can take steps to circumvent these disruptions.
SLAs and Outcome-Based Agreements
Outcome-based agreements and SLAs tell the customers what to expect from the organization
The threshold for a successful Field Service Organization is often defined by how well they meet their SLAs (service-level agreements). Outcome-based agreements and SLAs tell the customers what to expect from the organization. When users fall short of meeting these expectations, user can lose valuable business, earn a poor reputation for the organization, and find unhappy customers.
Without AI technology, outcomes can become harder to predict making outcome-based agreements challenging to fulfill. Whether the agreements involve providing customers with improved machinery performance, uptime, or health, users first need direct insight into the equipment.
real-time data updates
AI technology can give users the comprehensive equipment information user need as well as real-time data updates about any changes. Field Service AI technology (such as Bursys’s EquipConnect) continuously provides users with the key metrics user need to support the service contracts.
When a critical fault is detected, this technology can create an automatic service request and enable remote service to help users meet the agreements. Using real-time data analytics and reporting features, users can then communicate the outcomes to customers with ease and transparency.
Avoiding Schedule Disruptions
AI technology continuously gathers data to help users make informed decisions relating to resource planning
AI technology continuously gathers data to help users make informed decisions relating to resource planning. This data includes comprehensive information about predictable performance conditions requiring planned work orders, job requirements, and personnel scheduling.
Monitoring and analyzing equipment operating conditions using AI allows service organizations to proactively coordinate the scheduling of services with customers during production idle times preventing unexpected disruptions.
FieldEquip Field Service AI Technology
Are users ready to enable the field service organization to provide proactive and predictive service to its customers? EquipConnect from FieldEquip is here for the user.
Using the latest technology, FieldEquip field service software offers innovative AI solutions. This comes in addition to our comprehensive field service software capabilities.