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Sustainable business model for a predictive maintenance monitoring center

We are assembling an ongoing advisory board to discuss the best practices in developing sustainable business models for predictive maintenance and monitoring of core equipment across various processing industries (Chemical, Pharma, Food, etc.).

In this high-caliber online panel of 15 experts, you'll have the opportunity to learn collaboratively and advance innovation in the field.

Content will remain closed and confidential to participants. You are only committing to participate once per week (approximately 15 min.) or as inspired, at your convenience.

peopleExpert participation

- Maintenance and Engineering managers
- Experience in implementing and operating predictive maintenance centers
- Preferably users of platforms like GE Predix, Siemens MindSphere, Thingworx, Sight Machine, etc.

Applicants
Duke Sulliv
Digital and IoT Solution Sales and Operations Executive
I have rich experience and expertise in go-to-market, business process, Internet of Things (IoT), data strategy, architecture, and analytics - the confluence of which is driving business transformation in today’s digital age. I have 15+ years of management consulting experience with firms such as CSC, NerveWire, and Wipro Consulting. I have another 4+ years of experience with IoT platform product companies (e.g., Axeda, PTC ThingWorx) where I was responsible for global strategy, executive relationships, program development, enablement, and business performance for Telco and service partners, including AT&T, Accenture, Deloitte, Gap Gemini, Infosys, Tech Mahindra, TCS and others. I have experience with business case development, scoping, and pricing of BP and IT outsourcing and managed services. I also have experience as a data architect and BI/DW solution architect. I have been involved in device data and meter analysis projects targeted at predictive maintenance and more recently monitoring machine learning based proof of concepts. Remote service and operational safety and efficiency are certainly the leading use cases for IoT. Device/asset data, and machine learning based projects lag, but are accelerating. Usage and fault monitoring, event correlation, and predictive analysis are critical for mission critical assets and operations.... the question is how far down stream? Predictive analysis will drive "preventative maintenance". The other question is where does service desk start and stop... very interesting topic.
Anand V
Consultant
Currently an Industrial IOT consultant and an Subject matter expert. Working on few of the consulting assignments in automation of the shop floor for automotive industry and Petro chemicals.The assignment is on the automation using computer simulation models with analytics as backend. The AI and machine learning helps to develop the algorithms for the predictive monitoring using dashboards - The tools used are tableau and SAP HANA. There is a significant development in the business model using predictive maintainence for IIOT as business case. The growth is pegged at 15% CAGR for next 5 years. Also with the significant development in 5G there will be a much more penetration in this subject area. Also participated in other IIOT discussions
Adam Napoli
Managing Partner
With almost 20 years experience in Enterprise Asset Management, Maintenance and Reliability Sales Leadership, and a global role with an industry and market leading IIoT platform focused on driving predictive and prescriptive analytics, I bring significant expertise in advising, selecting, and deploying solutions for heavy asset operators, such as those in the petrochemical industry. Transferring this knowledge to help decision makers become better informed and able to speak to, articulate, and launch IIoT transformation initiatives focused on predictive maintenance and condition monitoring. I can help provide guidance that turns technology and solution discussions into actionable steps and business outcomes to secure funding and executive sponsorship for IIoT engagements.
Filip Grujev
Analytical Systems Qualification Responsible at ALKALOID AD
I have 8 years experience in Maintenance,Preventive Maintenance,Qualification, Validation and Calibration of Analytical Instrumentation (Chromatography/Spectrometry) in Pharmaceutical controlled laboratories. All work must be done complying all relevant guidelines and standards (cGxP). All trends in industry must be followed and applied if an improvement can be made. This analytical instruments (HPLCs) are used also in petrochemical industry and I can provide valuable input through sharing of best practices.
Praveen Viswan
Software Solutions Architect
Exposure to challenges of Industrial IoT, currently working to implement solutions in the maritime sector + exposure to multiple IoT platforms including GE Predix. GE Hackathon winner for best intelligent environment app.
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“I like that I can do this when I have time,
and there is no set schedule.”


Eric Allen, Senior Manager, Supply Chain at EY

“I find the topics engaging and I love the
flexibility of checking in and providing insights
at my convenience.”

Kimberly Underwood, Consultant at Underwood Consulting

“Great platform, great questions and topics.
The potential to earn a little more money for
participating is nice as well.”

Oren Birks, Sr. Director of IT at PBI-Gordon

“I really enjoy being on the panels, sharing
information and reading the perspective of the
other panelists. It is quite intriguing and most
all of the panelists are quite bright.”

Patty Soltis, CX Strategist at Kinetic Edge Consultants

“Very interactive, informative and without
any inherent bias. This is as good a collaborative
platform as you can get.”

Pinaki Banerjee, Program Director at ITC InfoTech

“It is a perfect platform not just to share
but to learn and stay updated.”


Armando Leyva, HR Director at 360º HC

FAQ
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  • add remove Are there specific times I need to participate?
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  • add remove How do KnowledgeStreams and DesignSprints work?
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Sustainable business model for a predictive maintenance monitoring center