HEAVY MACHINERY

COMMON SERVICE CHALLENGES FOR HEAVY MACHINERY

Heavy equipment is found in industries such as Mining, Agriculture, Construction, Cranes/Rigging, Steel, Energy/Power, Oil & Gas, Chemicals, Manufacturing, Aviation, Marine and more. Each of these industries provides mission critical services that depend on heavy equipment. If any one of these assets are not working, significant financial impacts will result at staggering amounts each hour. These accumulated impacts can be felt downstream with multiple parties affected. Heavy machinery, while durable, is often exposed to extreme conditions. To continue to design for industry needs, the manufacturers of the heavy equipment need to be informed of all the operating conditions and scenarios of exposure. However, it can be a challenge to obtain the real-time and relevant data because of the remote and extreme conditions. Manufacturers and operators need smarter and ruggedized digital solutions to ensure machine reliability and performance while reducing maintenance costs. 

Modern Field Service solutions such as Service Cloud, Salesforce Field Service and ServiceMax efficiently manage core service operations like providing customer support, generating work orders, creating entitlements, and dispatching technicians. However, other service challenges require connected assets and AIoT solutions, such as knowing exactly when to service equipment to avoid failures, minimizing service response and repair times, enabling equipment Servitization and remotely supporting machine operators.

These challenges were the catalyst for Connected Field Service. Connected Field Service enables organizations to transform the way they provide service from a costly break-fix model to a proactive and predictive service model by combining IoT diagnostics, asset management and resource management on an integrated service platform.

Customer Journey

Heavy machinery manufacturers partner with Spoke AIOT to connect their field-based capital assets to their Service Management solutions to improve asset reliability, enhance Call Center support, and reduce service costs. Partnerships typically begin with Visioning and Value Determination sessions to identify various ways that IoT and AI can create value and improve service outcomes. As Use Cases are defined, business benefits are estimated based on actual business performance data and industry value metrics. In parallel, an evaluation of asset connectivity options, machine trajectory data, and security risks is conducted to confirm the technical viability of achieving the defined Use Cases. Once technical viability is confirmed and business benefits are defined, Spoke AIOT partners with customers to define deployment plans and implementation cost estimates.

AIoT projects are most successfully delivered in smart phases. Typically progressing from single-asset pilots to full asset family deployments, to regional deployments, to national deployments, and beyond. Governance checkpoints between deployment phases generally require evidence that technical goals have been achieved and business value has been confirmed.

It’s common for heavy machinery to have multiple onboard sensors and integrated connectivity capabilities that make machine data available for consumption. To enable edge connectivity, Spoke AIOT installs virtual and physical gateways to enable and securely govern data connectivity between heavy machinery, the AIoT Cloud, and Service Management solutions. Once the data is flowing, Spoke AIOT’s out-of-the-box service tools quickly enable remote performance monitoring, anomaly detection, predictive analytics, digital twin visualization, and service workflow automation.

In cases where heavy machinery manufacturers already manage an installed base of connected assets and an IoT-cloud for collecting machine data, Spoke AIOT helps them integrate their IoT Cloud solution to their service management and ERP systems. Spoke AIOT’s out-of-the-box service tools quickly augment existing remote performance monitoring capabilities by delivering no-code service workflow automation. These capabilities combine to ensure the field-based assets are operating properly and enable appropriate service responses. Spoke AIOT extends the value of previous IoT investments by providing the capabilities needed to deliver the “last mile” of Connected Field Service.

Remote performance monitoring ensures heavy machinery operates as expected. As anomalies are detected, Spoke AIOT immediately notifies the right people to ensure the proper service response is coordinated. As machine data is gathered over time, advanced analytics begin to identify performance trends, predict asset failures, and recommend the best course of action to avoid unplanned downtime. In the field, the service technicians have access to real-time and historic asset data to quickly triage and resolve device issues. Starting with a single asset class, heavy machinery manufacturers can rapidly scale Spoke AIOT to multiple asset families around the world.

How Spoke AIoT helped this Customer

     Remote Connectivity

Remote work locations and “big data” transmission requirements are common inhibitors for heavy equipment manufacturers adopting AIoT solutions. Spoke AIOT solves this issue with its unique, modular, gateway architecture. Spoke AIOT partners with manufacturers’ product engineering team to spec out and deliver industrial gateways that enable edge processing and cloud connectivity; enabling heavy machinery to locally cache its big data, process AIoT rules and algorithms, and communicate with the Cloud in real time.

    Contract SLA Validation (Servitization)

Heavy machinery commonly carries a Service Level Agreement specifying equipment uptime and service response times. Manufacturers frequently struggle to validate equipment uptime; creating the risk of contract penalties and lost revenue. Spoke AIOT enables the equipment manufacturers to automatically generate an equipment health report appended to the lease invoice as evidence that the uptime SLA was achieved. When unplanned downtime occurs, Spoke AIOT’s real-time alerts minimize the manufacturer’s service response times; ensuring adherence to service response SLAs.

    Enhanced Call Center Support

With access to real-time, visualized, equipment data, manufacturers’ call center agents can better support customer issues. By opening the asset record in the service management solution, call center agents can view 2D and 3D renderings of the equipment with real-time performance data overlays and AI-recommended next steps. With Spoke AIOT, call center agents can resolve more customer cases in less time and without dispatching service technicians.

    Remote Monitoring & Alerts

With access to real-time device data, Spoke AIOT remotely monitors heavy equipment performance to improve operating reliability, prevent unauthorized usage, and reduce service response time. Spoke AIOT can be configured to provide real-time notifications when performance anomalies are detected; enabling manufacturers to proactively communicate observations and coordinate recommended services. Similarly, Spoke AIOT can be configured to provide notifications to equipment managers if the machine operates outside of the specified geo-fence or planned work hours. To avoid false positives, Spoke AIOT partners with manufacturers’ engineering teams to define data cleansing and validation protocols to ensure a focus on the right messages.

    Analytics and Predictive Maintenance

As Spoke AIOT captures and analyzes machine data over time, system analytics predict asset failures and recommend service responses. For customer-owned equipment, Spoke AIOT automatically creates sales opportunities and notifies manufacturers’ selling teams of the opportunity to sell parts and service. For leased equipment, Spoke AIOT automatically coordinates manufacturers’ service activity. Receiving intelligent preventive maintenance recommendations reduces the risk of equipment breakdown and larger service expenses while analytics support strategic decision-making to optimize the performance of the overall business.

    Service Automation

As real-time machine data identified performance anomalies, Spoke AIOT considers the context of the equipment when automating the service response. Whether the equipment is customer-owned or leased, the customer account type and financial status, equipment entitlements, and other relevant information all factor into how service for an asset must be coordinated. Spoke AIOT partners closely with equipment manufacturers to tailor the solution to support each service scenario, driving efficiencies across the back office.

    Asset Traceability (geo-location)

Using equipment latitudinal and longitudinal information in IoT data streams, Spoke AIOT can plot each machine locations on a map with high precision. Equipment geo-locations help service technicians locate machines in the field and enable alerts when equipment is not in the planned location. Spoke AIOT also uses geo-locations and data stream timestamps to correlate equipment environmental conditions in predictive algorithms. Because equipment theft is prevalent, manufacturers can offer a differentiated “goodwill” service by helping customers recover stolen equipment.

    Service Outcomes

When service technicians are required to be on-site, access to both real-time and historic device operating data helps them quickly and accurately diagnose and resolve issues. Heavy equipment manufacturer can enable their field service technicians with the Spoke AIOT mobile app to see real-time and historic performance data in the triage process. With these new insights, service teams can quickly identify root causes, spend less time diagnosing an issue, and improve their chances of fixing the issue correctly the first time. Heavy equipment manufacturers commonly report improvements to their Mean Time to Repair (MTTR) and First Time Fix (FTF) metrics. Service teams also reports higher service technician job satisfaction and loyalty resulting from the adoption of modernized service capabilities.

     Beyond Service

There are several opportunities for heavy equipment manufacturers to leverage Spoke AIOT beyond service. Monitoring equipment usage for extreme loads or usage beyond duty cycles can help defend warranty claims. Also, having access to real-time and historic device operating data provides product engineering teams with deep insights that drive next-generation product improvements. Most importantly, Spoke AIOT can identify instances of asset utilization exceeding planned capacity and automatically creates sales opportunities to expand an installed base.

Solution Summary & benefits

Today, heavy equipment manufacturers and their customers are seeking smart and unified solutions that can improve asset uptime, reduce total ownership costs, comply with regulatory requirements, protect the environment, and ensure safety. Spoke AIOT can help manufacturers connect, analyze and act on equipment data, delivering the benefits of Connected Field Service. Talk to an expert at Spoke AIOT to learn more about how connected assets and AIoT-enabled solutions can transform your heavy equipment business.

 

  • Improved asset uptime/reliability
  • Improved call center effectiveness
  • Reduced service costs
  • Reduced service response time
  • Improved First Time Fix (FTF)
  • Improved workforce productivity & utilization
  • Improved parts inventory forecasting
  • Enabled new service revenue models
  • Provided deep insights to support other business functions

The future is AIoT enabled Service

Artificial Intelligence can exponentially increase the value of IoT by using all the data from the asset/install base to accurately predict outcomes and promote a collective intelligence.

Trillion ECONOMIC VALUE WILL BE CREATED BY AIOT ENABLED SERVICES BY 2025

%

EXECUTIVES CURRENTY USING AIOT ARE EXCEEDING EXPECTATIONS FOR THE VALUE

%

EXECUTIVES BELIEVE AIOT WILL ENABLE THEM TO ENHANCE PRODUCTS & SERVICES OVER THE NEXT 3 YEARS

%

MANUFACTURERS’ COMPLEX EQUIPMENT WILL EXECUTE IOT-ENABLED SERVITIZATION STRATEGIE BY 2025

%

INDUSTRIAL MANUFACTURERS EXPECT TO AIOT FOR PREDICTIVE MAINTENANCE BY 2022

%

MANUFACTURERS CURRENTLY EITHER USING OR PILOTING IOT IN PRODUCTION