1S7a: (20 min.) Case Study: Cost Effective Implementation of PdM for Commercial and Industrial Facilities

Artem Kroupenev, VP of Product, Augury


Predictive Maintenance (PdM) is used to detect the onset of mechanical failure allowing for corrective action to be taken before significant or catastrophic failure of the equipment occurs. Adoption of PdM across commercial and industrial facilities has traditionally been low due to high costs and extensive training and expertise required to implement a program. Through the adoption of Augury’s PdM diagnostic tools, industrial facilities have been able to bring PdM to the entirety of each facility and implement a lasting program on a larger scale. With Augury’s technology, mechanical data is automatically uploaded to the cloud, where machine learning algorithms process that data and diagnose the state of the equipment. Initial diagnostic results are accessible in real-time, and users are provided with actionable results and maintenance suggestions to optimize their machines.

In this talk, we will show how one customer created a PdM Program using Augury to reduce system failures and related downtime, minimize disruptions, reduce energy, reduce capital and labor cost while optimizing the life cycle of Tier 1 assets.


Artem is Head of Product at Augury, where he oversees the development of Augury’s current and future machine diagnostic and predictive maintenance solutions. He has over 10 years of experience in product, innovation and business development, and has co-founded and helped grow enterprise-focused startups in Israel, New York and West Africa. Prior to joining Augury, Artem was entrepreneur in residence at Bionic, a leading enterprise innovation consultancy based in NYC. In his previous roles, he served as Co-founder and COO of Choozer, and Co-founder and VP Product of HDID. Artem holds and BA and MA from IDC Herzliya in Israel.