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Lumber Digital Process Optimization Manager


GP Lumber Division is seeking a talented individual for our Digital Process Optimization Manager role. Headquartered in Atlanta, Georgia-Pacific is one of the world’s leading manufacturers and marketers of building products, tissue, packaging, paper, cellulose and related chemicals. The company employs more than 30,000 people at approximately 300 locations in North and South America.

What You Will Do In Your Role

  • Developing and managing a data center manufacturing environment
  • Assisting the facilities with using data to build a centralized data analytics and remote monitoring capability
  • Identifying data gaps needed to improve asset health or process resolution on existing and new equipment
  • Networking with the GP Collaboration Center (CSC) to develop automated notifications/alerts real time based on data analytics/AI to maintain and improve asset performance.
  • Collaborating with the plant sites frequently, providing insights on trends and or alerts that need to be investigated and or acted upon.
  • Working with division and plant resources to identify and integrate new monitoring systems and analytics platforms.
  • Establish a collaboration network with the site DPO Leaders.
  • Asset and or process deviations automatically flagged, tracked and resolved timely. Over time plant DPO evolves such that remote service capability is a core capability of manufacturing as it relates to early detection of a process shift or asset starting to show signs of premature failure.
  • Support continuous improvement processes through decision making, facility engagement, as well as developing new monitoring systems and providing training.
  • Using data to assess and improve equipment & process capability, leverage sustained best practices from plant-to-plant, and communicate and present data effectively.
  • Working collaboratively work and communicate with data scientists, various data software platforms, IT resources, and plant personnel from plant managers to plant operators.
  • Accelerate the pace of defining and implementing best equipment operating practices and standards across the platform. 
  • Use data and digital tools to more quickly identify and intercede in our operations to avoid losses in the form of downtime, loss of productivity or other value opportunities.
  • Travel to GP’s 16 different Lumber Facilities to build relationships with operations, roll out new monitoring platforms and assist solving plant issues

The Experience You Will Bring


  • At least 5 years of data analytics experience with a statistical background, experience MUST include data mining, using data to influence business partners, mentoring site analytics capabilities
  • At least 5 years of technical leadership experience in a manufacturing environment, experience MUST include:
    • Leading a Continuous Improvement team or conducted Kaizen events
    • Management of facility technical department
    • Experience with maintenance, reliability, manufacturing process best practices
    • Mentoring/coaching/developing facility leadership
    • Must travel up to 50% (including some overnight travel)

What Will Put You Ahead

  • Bachelor’s Degree or higher in Engineering

  • Experience with Process Engineering (5S, DMAIC, Kaizen, value-stream mapping, etc.)
  • Experience with the application of Lean Six Sigma methodologies
  • Experience with data management, software tools, and Process Control fundamentals (PLCs, DCS, PI, SAS, Envoy, JMP, MatLab, etc.)
  • Experience with IoT and digital transformation
  • Experience with mechanical reliability fundamentals (RCA, Maintenance programs, etc.)
  • Experience with managing projects / initiatives and working with plant operations to integrate

Salary and Benefits Commensurate with Experience.
Equal Opportunity Employer.
Except where prohibited by state law, all offers of employment are conditioned upon successfully passing a drug test.

This employer uses E-Verify. Please visit the following website for additional information:www.kochcareers.com/doc/Everify.pdf


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