At Clockwork Solutions, we have over 25 years’ experience providing software solutions that help enterprises get the most out of their strategic assets. Our advanced predictive analytics platform can help you discover the hidden value in your data to answer your million dollar questions.
We work with enterprises across industries, ranging from aerospace and defense to construction, manufacturing, and transportation. Our team collaborates with asset managers, equipment manufacturers, and contractors who are seeking ways to leverage predictive analytics to solve their largest obstacles.
We are proud to have worked have worked with leaders across industries and around the world, including…
With hundreds of studies and deployments around the world, our team has the experience to help you address your tough questions. Don’t see your use case below? Contact us today and find out how we have helped organizations like yours succeed!
A supplier of military aviation hardware required optimization of their Performance Based Logistics costs for sparing based on several KPIs; including Operational Availability, Time on Wing, and the cost per flight hour.
By modeling the fleet by components over a 12 year period we were able to optimize sparing based on reliability, operations, maintenance concept, and component aging.
Clockwork was able to show a $683M reduction in LCC for parts, reducing the cost per flight hour by over 70%.
A defense program was looking to optimize inventory levels over a 7-year period for a fleet of 2,000 trucks, each with 900+ mission critical parts.
Using simulations and predictive analytics, Clockwork evaluated future performance based on over thirty 7-year high resolution scenarios to optimize inventory allocation and costs.
The optimal scenario resulted in over $50M of cost avoidance while increasing fleet availability to over 95%!
Clockwork teamed with DoD and commercial partners to evaluate the impact of CBM to the reset program of a fleet of mobile generators.
Using a comprehensive Predictive Analytics / Discreet Event Simulation model, Clockwork was able to compare multiple scenarios with and without CBM to build a Business Case Analysis
The analysis showed that while CBM would reduce the need for a reset by 25% and the total cost of a reset by 11%, it also revealed a solution not previously considered. Adding 1-3% additional generators delivered a lower cost solution vs the planned reset and the same gains as a full CBM implementation and resulting in hundreds of millions of savings.
An operator of a fleet of drilling ships needed to optimize the lifecycle of 6 drill ships that were operating across 3 different countries for equipment overhauls as well as a corresponding critical spares buy plan by time and location.
The Clockwork platform was able to capture the complex configuration and mission profile of each ship to evaluate future performance of and calculated revenue per ship based on a 15-year life cycle.
The resulting analysis delivered $2B in additional revenue across the fleet while insuring target availability for all ships through the life cycle.
A manufacturer of packaging equipment deployed in thousands of locations worldwide required a PHM solution to address customer satisfaction issues due to long lead times for maintenance when equipment failures occurred.
Clockwork derived a PHM solution where data is collected every few minutes reporting on multiple sensors. This data was then combined historical data and subjected to an analysis including anomaly detection, anomaly classification and diagnosis and failure mode prognostics.
The resulting PHM implementation was able to provide multi-month warnings regarding impending failures on multiple components.
A major electric utility needed to determine the optimal amount of spare transformers to ensure minimal down-time. With a cost per unit exceeding $500,000 and up to a year lead-time, the costs of a wrong decision were either an expensive and unproductive resource allocation or downtime and loss of revenue. Based on traditional, non-analytical methods, the utility estimated that they required 30 transformers at a cost of $10M.
Using historical data collected over a 15-year span along and applying the effects of real-world factors such as lead times and repair times, Clockwork developed a model that provided a comprehensive set of what-if and sensitivity analysis.
The model determined that the number of number of transformers required to meet the utility’s performance objectives was in fact two not 30 with total savings to the company amounting to nearly $9 million.
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