Manufacturing Data Analytics Summer Intern

At MB, an Aebi Schmidt brand located in Chilton, WI, we pride ourselves on innovation, collaboration, and dedication to excellence. As part of the Aebi Schmidt Group, we are committed to delivering superior solutions to our customers as well as providing rewarding career opportunities.

Position

The Manufacturing Data Analytics Summer Intern will aid in data tracking, and entry, data analysis and reporting within our manufacturing facility, contributing to continuous improvements while gaining practical career experience.

Responsibilities

Gather, organize, and analyze data to give visibility to management and department stakeholders to aid in understanding defect sources, tracking, and solutions. This includes reviewing manufacturing processes to understand how defects are generated as well as creating and sustaining data analysis routines to provide continuous monitoring of quality metrics.

• Interact with representatives from a variety of functional groups, including design engineering, manufacturing engineering, purchasing, and all production and inspection personnel in the facility.
• Data tracking and entry on defects, failures, and warranty claims.
• Perform data analysis to identify trends, patterns, and potential issues in manufacturing processes or systems.
• Assists in creating reports to present data on quality trends and metrics.
• Assists in identifying the root causes of a problem and instituting corrective action such as changes to operation sheets, generation of “Engineering Change Requests, installation of fixtures, changes in workstations, changes to inspection analyses and changes to process procedures.
  
  
  

Qualifications

• Professional communication and interpersonal skills.
• Proficient in Microsoft Excel tables, formulas, and charts.
• Strong analytical and problem-solving skills.
• Ability to work in a manufacturing facility around running equipment and follow all safety requirements.
• Ability to work at a desk for extended periods of time.
• Interest in manufacturing and large machinery.
• Pursuing a degree in related field (e.g., engineering, data science, statistics)