City Scape

Democratizing Predictive Maintenance through the Industrial Internet of Things

Content and Description

Content View
Viewable / downloadable shared learning appears here for logged in members only.
Content Description
Original date: 
Wednesday, February 28, 2018
Abstract: 
With all the talk about big data and the IIoT, many are asking how can we use this in maintenance? The IIoT enables us to put sensors in any location where we might want to collect and analyze equipment condition and performance data. There are companies that offer predictive maintenance services, and some companies do this for themselves, in-house. Typically, it’s the larger companies that can afford this, but democratization has meant this has become available to a much broader market. But there are hurdles to taking advantage of this sort of continuous monitoring program, even for your most critical equipment. One, it’s expensive, whether you do it in-house or outsource. And two, there are data bottlenecks. Condition monitoring data comes is huge volumes and it’s all time-sensitive. Even if you can afford it, you need a data handling network with a lot of capacity. In this workshop, we’ll present a viable technical solution to the data bottleneck problem — based on a solution already proven in financial securities markets — that opens up these possibilities in the realm of plant continuous condition monitoring.
BoK Content Source: 
MainTrain 2018
BoK Content Type: 
Supporting Slides
Paper
Asset Management Framework Subject: 
00 Asset Management - General, 1.00 Strategy and Planning General, 02 Asset Management Decision Making, 2.02 Operations & Maintenance Decision-Making
Maintenance Management Framework Subject: 
00 Maintenance Management - General, 01 Business & Organization Context, 1.0 Business & Org Context General, 1.1 Requirements & Expectations, 1.2 Enablers & Constraints, 1.4 Strategic Maintenance Plan, 02 Maintenance Program Mgmt, 2.0 Maintenance Program Mgmt General, 2.1 Maintenance Requirements, 2.2 Organizational Structure, 2.4 Maint. Budget/Cost Control, 2.9 Outsourcing, 03 Asset Strategy Management, 3.0 Asset Strategy Management General, 3.2 Performance Measurement & Optimization, 04 Tools and Tactics, 4.0 Tools and Tactics General, 4.1 Reliability Centered Maint., 4.2 Preventive Maint. Optimization, 4.4 Preventive Maintenance, 4.5 Detective Maintenance, 4.6 Condition Monitoring, 4.8 Predictive Maint. Techniques, 5.0 Maintenance and Reliability Eng General, 5.1 Stats Analysis / Analytical Methods, 5.2 Reliability Modelling, 10 Continuous Improvement, 10.4 Maintenance Practices Improvements, 10.5 Asset Reliability Improvements
Publisher: 
Kx Ssystems, Inc.
Edition or Version: 
n/a
ISBN: 
n/a
Author Title: 
Principal Consultant
Author Employer: 
Conscious Asset
Author Bio: 

James Reyes-Picknell is principal consultant at Conscious Asset, a specialist consulting and training firm that helps companies increase productivity, decrease costs, and get the most value from their physical assets. James has more than 40 years of experience in asset management, engineering, and consulting. He is based in Ontario, Canada.

Author 2 Title: 
Senior VP IIoT and Utilities
Author 2 Employer: 
Kx Systems, Inc.
Author 2 Bio: 
Przemek Tomczak has more than 20 years in IT and business leadership, implementing and operating big data and analytics systems, delivering program and transformation initiatives, consulting, outsourcing, and risk management in the energy and utility and other industries. Przemek was responsible for the implementation and operation of world’s first and largest smart meter data management system for 67 utilities and five million end customers. Previously, Przemek held senior roles at the Independent Electricity System Operator in Ontario, as well as Canadian top-tier consulting firms and systems integrators. Przemek also holds the CPA, CA, and CISA designations.