Hack X

Overview: Empowering the decision maker on how to progress through their career. Manager can see aggregated list of an employee’s career journey. Individual employee can see the requirements of what it takes to move from one level to the next in their career journey.

Deliverables:

Propose and design a solution that will carry out the following tasks at the minimum:

• What skills sets an employee needs to have to progress within a specific skills trade. As an example, Entry-level welder to Mid-career welder.
• Provide both the employee and manager the ability to scan and upload certifications of a plant employee.
• Provide the employee the opportunity to create their profile and upload all their relevant skills set at each stage of their career journey.

Deliverable/solution solves these pain points:

• A plant manager not having a complete view of the level of expertise for any given job within a manufacturing plant.
• The desire of plant employees to have transparency into what it takes to move up the ranks within their job specification e.g. Go from entry-level welder to experience welder.

Submission: A solution that seamlessly manages the skills and carrier journey of a manufacturing employee.

Brownie points for using AI; Brownie points for using predictive and analytical modules

Overview: It is challenging to efficiently run a manufacturing plant by depending on outdated data and information that resides in siloed systems and database. The goal of this intelligent plant productivity system is to track and combine data from multiple systems – safety, delivery, availability, performance, and quality—to produce an Overall Equipment Effectiveness score (OEE score).

Deliverables:

Propose and design a solution that will carry out the following tasks at the minimum:

• Capture plant quality data generated by multiple process within a manufacturing plant.
• Capture machine and process data and generate relevant plant KPI measures – Safety, Quality, Delivery, Cost, Operational efficiency.
• Capture machine performance data and generate relevant metrics for machine availability and performance.
• Analyze and synthesize information across multiple data set and KPIs and highlight relevant patterns.
• Based on synthesized data, recommend actionable steps to take to improve OEE (availability, performance, and quality)

Deliverable/solution solves these pain points:

• Lack of Productivity improvements driven by data science.

Submission: A solution (e.g., a web-app, API, or tool) that can intelligently identify areas of improvement within a manufacturing plant data set and suggest opportunities for improving plant OEE numbers.

Brownie points for using AI; Brownie points for using predictive and analytical modules

Overview: There is organizational knowledge loss when skilled employees retire or leave the company. This issue is caused partly by not having a centralized knowledge repository or not taking time to capture new work instructions that have been developed on the job. Loss of critical knowledge is especially an increasing problem as the baby boomer generation retires from the work force. Critical knowledge could be in the form of videos, work instructions, pictures, diagrams, etc.

Deliverables:

Propose and design a solution that will carry out the following tasks at the minimum:

• The system should allow the user to upload a pdf, a jpeg file or video file as the input.
• Ability to scan and capture paperwork instructions into a digital format
• Ability to search text and other relevant information in captured data

Deliverable/solution solves these pain points:

• Inability to quickly train and retain talent
• Little to no systematized way of retaining critical knowledge

Submission: A solution (e.g., a web-app, API, or tool) that can intelligently identify, capture, and organize critical knowledge like, work instructions, diagrams, videos of a job, etc.

Brownie points for using AR/VR; Brownie points for using predictive and analytical modules