In 2018, Ford Motor Company was forced to halt production of its F150 pickup truck following a fire at the facility of a part supplier. The F series line of trucks was among the top-selling vehicles in the US at the time, and estimates suggest Ford could have lost millions in revenue for each day of lost production. The potential revenue impact was such that Ford did not hesitate to extract crucial equipment from the plant, install it in a plant in the UK, and fly the fabricated parts back to the US at a significant cost. In the manufacturing business, every minute lost to such equipment breakdowns eats away at profits, delays customer orders, and disrupts supply chains.
It may seem surprising that even in today’s increasingly digitized world of automation and AI, unplanned downtime continues to plague factories. According to a study by Siemens, unplanned downtime in 2021-22 cost Fortune Global 500 companies nearly $1.5 trillion (11% of their yearly turnover). In the FMCG sector, a lost hour can amount to a loss of $39,000. In the automotive sector, this can be as high as $2 million.
So, why haven’t we cracked the code on this costly problem? The answer often lies in the most fundamental yet overlooked element of modern manufacturing — data.
The Disconnected Factory Floor
Most manufacturing operations utilize multiple machines, applications, and processes. Unfortunately, the data generated by these individual components in the manufacturing system frequently exists in silos. This fragmented data obscures important relationships between factors such as equipment health, energy consumption, maintenance schedules, and production bottlenecks.
Without a comprehensive picture, manufacturers are forced to tackle unplanned downtime based on incomplete or even misleading insights. They may address symptoms rather than root causes, resulting in temporary or ineffective solutions.
An End-to-End Data Solution
The key to eliminating unplanned downtime doesn’t just lie in more data — it’s about connecting the dots to paint a complete operational picture. This is where a holistic data strategy comes into play.
Acuvate has designed a 7-step framework that unifies data to solve pain points across industries. In manufacturing, the framework collects and integrates data from across the factory floor, transforming fragmented bits of information into a powerful decision-making tool. Here’s how the framework orchestrates this powerful data-to-value pathway:
Critical device monitoring:
Time-series data from all critical assets (engines, turbines, compressors etc.) is systematically collected along with maintenance history from ERP sources. This lays the foundation for comprehensive analytics by incorporating multiple related data streams.
Fast and reliable data transfer:
The acquired data is seamlessly transmitted in real-time using technologies like 5G, WiFi or LPWAN based on infrastructure and criticality requirements. Quick, reliable data transport enables proactive interventions before minor issues escalate.
Efficient data processing:
Data is intelligently processed at the source through edge gateways and analytics, minimizing latency for detecting anomalies indicating potential failures. Compute happening close to the asset reduces time to insight.
Centralized cloud storage:
Aggregated data from all sources is securely streamed to a centralized cloud data platform. This unified data repository enables deeper analysis by correlating signals across the entire manufacturing operation.
Effective AI-driven insight generation:
Advanced AI/ML models running on the cloud data platform convert multi-source inputs into predictive maintenance insights, identifying components at risk of failure and prescribed actions to mitigate.
Actionable information for stakeholders:
Consolidated dashboards arm plant managers and executives with a real-time unified view of asset health KPIs, risk exposure, and the operational impact of maintenance activities.
Useful recommendations for predictive maintenance:
AI-driven recommendations for critical component inspections/replacements flow directly to maintenance teams based on criticality scoring, ensuring optimal resource allocation. Generative AI and Extended Reality-based apps provide simple visualization for data-driven decisions.
The Proof in Action: Helping a Consumer Goods Juggernaut Build Sustainable Processes
The true power of this approach is evident in its real-world impact. Acuvate’s partnership with a British multinational consumer goods giant showcased how data can drive both efficiency and sustainability.
The client wanted to further its sustainability goals by digitizing its supply chain and manufacturing processes. To achieve this, it was crucial to maximize machinery throughput and utilization, meet ideal production time, and efficiently monitor equipment effectiveness. Relying on the 7-step framework, Acuvate provided a turnkey data solution leveraging IoT, Azure SQL, PowerBI and AI/ML models to monitor Overall Equipment Effectiveness (OEE) across global factories.
The results were game-changing:
- 20% OEE increase across several manufacturing units
- Improved process reliability
- 8% enhancement in output reliability
- Significant labor productivity gains
- Approximately 4,000 person-hours saved per month through automated reporting
As this example shows, the path to eliminating issues like unplanned downtime is turning fragmented data silos into a seamless data-to-value pipeline. Powered by the latest advances in connectivity, edge computing, centralized AI/ML, and Acuvate’s proven 7-step framework, manufacturers can achieve the dream of self-optimizing, predictive operations and facilities.
The New Dawn for Manufacturing
The manufacturing industry is entering a phase of uncertainty. The advent of ‘Industry 4.0’ has led to marginal improvements in reducing the number of incidents and downtime. Simultaneously, global supply chain challenges and scarcity of skilled labor present obstacles to unlocking more efficiency. In this climate, advanced tools and expert implementation are needed to leverage data and avoid expensive downtime events. Acuvate’s end-to-end approach ensures that no piece of data goes unutilized, transforming factories into streamlined, efficient, and profitable operations.
Want to discover how an integrated data strategy could transform your operations and put an end to unplanned downtime? Reach out to Acuvate today to take the first step towards manufacturing excellence.
In 2018, Ford Motor Company was forced to halt production of its F150 pickup truck following a fire at the facility of a part supplier. The F series line of trucks was among the top-selling vehicles in the US at the time, and estimates suggest Ford could have lost millions in revenue for each day of lost production. The potential revenue impact was such that Ford did not hesitate to extract crucial equipment from the plant, install it in a plant in the UK, and fly the fabricated parts back to the US at a significant cost. In the manufacturing business, every minute lost to such equipment breakdowns eats away at profits, delays customer orders, and disrupts supply chains.
It may seem surprising that even in today’s increasingly digitized world of automation and AI, unplanned downtime continues to plague factories. According to a study by Siemens, unplanned downtime in 2021-22 cost Fortune Global 500 companies nearly $1.5 trillion (11% of their yearly turnover). In the FMCG sector, a lost hour can amount to a loss of $39,000. In the automotive sector, this can be as high as $2 million.
So, why haven’t we cracked the code on this costly problem? The answer often lies in the most fundamental yet overlooked element of modern manufacturing — data.
The Disconnected Factory Floor
Most manufacturing operations utilize multiple machines, applications, and processes. Unfortunately, the data generated by these individual components in the manufacturing system frequently exists in silos. This fragmented data obscures important relationships between factors such as equipment health, energy consumption, maintenance schedules, and production bottlenecks.
Without a comprehensive picture, manufacturers are forced to tackle unplanned downtime based on incomplete or even misleading insights. They may address symptoms rather than root causes, resulting in temporary or ineffective solutions.
An End-to-End Data Solution
The key to eliminating unplanned downtime doesn’t just lie in more data — it’s about connecting the dots to paint a complete operational picture. This is where a holistic data strategy comes into play.
Acuvate has designed a 7-step framework that unifies data to solve pain points across industries. In manufacturing, the framework collects and integrates data from across the factory floor, transforming fragmented bits of information into a powerful decision-making tool. Here’s how the framework orchestrates this powerful data-to-value pathway:
Critical device monitoring:
Time-series data from all critical assets (engines, turbines, compressors etc.) is systematically collected along with maintenance history from ERP sources. This lays the foundation for comprehensive analytics by incorporating multiple related data streams.
Fast and reliable data transfer:
The acquired data is seamlessly transmitted in real-time using technologies like 5G, WiFi or LPWAN based on infrastructure and criticality requirements. Quick, reliable data transport enables proactive interventions before minor issues escalate.
Efficient data processing:
Data is intelligently processed at the source through edge gateways and analytics, minimizing latency for detecting anomalies indicating potential failures. Compute happening close to the asset reduces time to insight.
Centralized cloud storage:
Aggregated data from all sources is securely streamed to a centralized cloud data platform. This unified data repository enables deeper analysis by correlating signals across the entire manufacturing operation.
Effective AI-driven insight generation:
Advanced AI/ML models running on the cloud data platform convert multi-source inputs into predictive maintenance insights, identifying components at risk of failure and prescribed actions to mitigate.
Actionable information for stakeholders:
Consolidated dashboards arm plant managers and executives with a real-time unified view of asset health KPIs, risk exposure, and the operational impact of maintenance activities.
Useful recommendations for predictive maintenance:
AI-driven recommendations for critical component inspections/replacements flow directly to maintenance teams based on criticality scoring, ensuring optimal resource allocation. Generative AI and Extended Reality-based apps provide simple visualization for data-driven decisions.
The Proof in Action: Helping a Consumer Goods Juggernaut Build Sustainable Processes
The true power of this approach is evident in its real-world impact. Acuvate’s partnership with a British multinational consumer goods giant showcased how data can drive both efficiency and sustainability.
The client wanted to further its sustainability goals by digitizing its supply chain and manufacturing processes. To achieve this, it was crucial to maximize machinery throughput and utilization, meet ideal production time, and efficiently monitor equipment effectiveness. Relying on the 7-step framework, Acuvate provided a turnkey data solution leveraging IoT, Azure SQL, PowerBI and AI/ML models to monitor Overall Equipment Effectiveness (OEE) across global factories.
The results were game-changing:
- 20% OEE increase across several manufacturing units
- Improved process reliability
- 8% enhancement in output reliability
- Significant labor productivity gains
- Approximately 4,000 person-hours saved per month through automated reporting
As this example shows, the path to eliminating issues like unplanned downtime is turning fragmented data silos into a seamless data-to-value pipeline. Powered by the latest advances in connectivity, edge computing, centralized AI/ML, and Acuvate’s proven 7-step framework, manufacturers can achieve the dream of self-optimizing, predictive operations and facilities.
The New Dawn for Manufacturing
The manufacturing industry is entering a phase of uncertainty. The advent of ‘Industry 4.0’ has led to marginal improvements in reducing the number of incidents and downtime. Simultaneously, global supply chain challenges and scarcity of skilled labor present obstacles to unlocking more efficiency. In this climate, advanced tools and expert implementation are needed to leverage data and avoid expensive downtime events. Acuvate’s end-to-end approach ensures that no piece of data goes unutilized, transforming factories into streamlined, efficient, and profitable operations.
Want to discover how an integrated data strategy could transform your operations and put an end to unplanned downtime? Reach out to Acuvate today to take the first step towards manufacturing excellence.
