endorsedOngoing

IoT Predictive Maintenance Platform for Mechademy Inc

Services Covered:

Custom Software Development • Cloud Consulting and Services • AI and Machine Learning • DevOps • Cybersecurity

Industry

Energy & Natural Resources

Duration

70 months

Budget

50K - 199K

Start Date

1 October 2020

Team Size

6-10 Employees

Engagement Model

Offshore

Project Capability Score (PCS)

70/100

Good

Project Capability Score (PCS) estimates how capable Daffodil Software is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Mechademy Inc

Houston, United States of America

Project Summary

Daffodil Software built a cloud-based, AI-driven predictive maintenance and remote monitoring platform for an engineering solutions company serving the oil & gas industry. They designed, developed, and deployed the infrastructure on AWS, integrated the client's machine-learning algorithms to analyze near-real-time sensor data, and advised on cybersecurity. The platform has begun to position the client as a product/service provider in industrial IoT and advanced analytics.

Key Challenges

Address unplanned downtime and system outages in Oil & Gas equipment
Ingest near-real-time time-series sensor data and run proprietary engineering and machine-learning algorithms
Provide prescriptive alerts and equipment performance predictions to enable optimized operations

Project Deliverables

Cloud-based remote monitoring platform
AWS-deployed infrastructure and optimized data flow
Data processing and machine-learning integration for predictive maintenance
Cybersecurity consultation and measures
Milestone-based releases with UAT and bug fixes

Project Solution

Daffodil conducted scope-finding sessions, prepared a detailed scope, and then designed, developed and deployed the platform infrastructure on the client's AWS cloud. They optimized services and data flows, integrated the client's machine-learning algorithms to process time-series sensor data, consulted on cybersecurity initiatives, and delivered the project in four milestones with 2–3 sprints each, currently in final UAT and bug-fix milestone.

Project Outcome

The platform has differentiated the client from an engineering consultant to a product/service provider in advanced analytics and industrial IoT
Clients have shown strong interest and the client expects to scale the business once the platform is fully deployed
Project management was effective with a proactive project manager and technical lead

Platforms

Cloud

Tech Stack

Amazon Web Services (AWS)

Client Endorsement

Overall Review Rating

4.38

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“The platform effectively differentiates the client in the advanced analytics and industrial IoT space. Internal stakeholders anticipate the solution to play a key role in scaling their business. The team thoroughly understood the requirements, transforming practical goals into functional features.”
Manav Bhargava
COO & Co-founder
Date: 06/19/2020