Contact person: Machinery Diagnostics Project -- 2

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Location: Minneapolis, United States

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"Project Overview
Cutsforth is assembling a development team to build out our new data analytics tool that will be a new product offering to our customers in industrial markets with critical assets. We’re engaging a flexible workforce of contract talent to help on the building side and as needed to manage and maintain the system as it rolls out.

Scope of Work
Key Responsibilities
• Product Development: Provide machinery dynamics knowledge along with Python coding skills to help in the development of a data analytics platform focused on critical machinery.
• Diagnostic Analysis: Apply expertise in vibration analysis, kinetics, rotor dynamics, electrical signature analysis, and time domain waveform analysis to diagnose machinery issues and ensure optimal performance and reliability. Knowledge of finite element analysis (FEA) is helpful but not a primary focus.
• Diagnostics Translation: Convert vibration analysis, rotor dynamics, electrical signature analysis, and waveform techniques into Python-based algorithms and models.
• Model Development: Build and validate machinery models using signal processing techniques for real-time diagnostics.
• Data Structuring: Organize diagnostic outputs into structured formats compatible with Cutsforth’s data repositories (e.g., Databricks).
• Technical Documentation: Create and hand off documentation for diagnostic algorithms, modeling assumptions, and code implementations.
• Procedure Development: Where needed, develop standard procedures for collecting and analyzing diagnostic data, including vibration, electrical, and kinetic data and share with Cutsforth Team accordingly.
• Collaboration: Confer with Cutsforth partners, vendors, or service providers to establish diagnostic specifications, resolve issues, and develop new diagnostic methodologies.
• Tool Enhancement: Recommend improvements to diagnostic tools and reporting formats based on field data and modeling insights.
• Methodology Improvement: Identify, recommend, and implement enhancements to diagnostic methodologies, tools, and reporting formats, including vibration analysis reports, electrical signature analysis outputs, and FEA models
• Software Development Support: Work under the Software/R&D Team to support the development of a strategic software platform for reliable diagnostic tools to meet customer asset management needs in the form of a sellable software product.

Deliverables
• Utilize unsupervised learning techniques to identify critical features in emerging failure modes.
• Assist Data Science Team in building and tuning ML models related to machinery health.
• Deliver Python ML models based on raw wave form and extracted data.
• Write and develop advanced pattern recognition (APR) tools.
• Identify and extract features.
• Create comprehensive diagnostic reports with graphical representations (e.g., frequency spectra, waveforms, FEA models).
• Utilize structure and maintain diagnostic data repositories using platforms like Databricks.
• Document recommendations for improvements to diagnostic tools, methodologies, and reporting formats.
• Write Python modules and scripts implementing diagnostic logic for asset types.
• Validate models (e.g., FEA, waveform analysis) with documentation.
• Contribute to the platform’s knowledge base and technical manuals." (client-provided description)