Clockwork’s predictive analytics for Enterprise Asset Management (EAM) solutions improve asset availability, optimize operating costs and reduce risk of unplanned maintenance, resulting in billions of savings and profitability.
Predictive Health Monitoring Framework
Clockwork’s Predictive Health Monitoring Framework (PHMF) allows clients to quickly assess the effectiveness and value of existing sensors onboard assets and formulate a strategy moving forward for maximizing that value.
PHMF utilizes a multitude of well-established mathematical techniques in conjunction with clients’ existing data in order to establish a feasible path to maximum value in reducing the costs of maintenance and inventory. Clockwork’s experienced Data Scientist team works with clients to identify, extract, and condition client data for use within PHMF in order to achieve these cost reductions in a sustainable way over the life cycle of the assets under consideration.
The value we drive for our customers, i.e. the Clockwork Advantage, comes from a unique combination of Platform Technology and Software & Project Services:
At the core of our solution is powerful technology. Our products provide life cycle asset-specific analysis rather than relying on generic trend data to make machine specific recommendations. The software is built using high fidelity risk simulations that have been perfected over decades of use in determining maintenance requirements for capital intensive assets. Unique to Clockwork is the ability to capture data at unlimited levels of indenture, making it easy to determine the component(s) that will have the most impact on reliability and performance.
Since inception, Clockwork Solutions LLC has served the global needs of over 30+ clients with mission critical requirements. Our customers represent a diverse base of capital intensive industries including aerospace, defense, energy, heavy machinery, and transportation. Our data scientists, software engineers, and leadership team have experience with the most complex applications and Big Data needs in the industry.