Production Planning & Sequence Optimization for a Polymers Manufacturer

Business Objective: Produce polymer grades at optimal levels to meet customer demand on time, maximizing revenue and minimizing switching costs Key Solution:
  • The solution provides Machine Learning (ML) based recommendation on optimum product mix to be targeted, in the form of a weekly production plan to maximize revenue
  • Using the production plan, it further recommends optimal manufacturing sequence on the production line to reduce costs and improve time to market
  • Various elements such as market conditions, plant conditions, technical constraints, inventory inputs, raw material supply and other production parameters were utilized to build the solution

Business Impacts & Outcomes:

  • Reduced number of transitions generating additional 190 MT monthly production
  • Increased EBITDA by 0.5 – 1%

Remote Plant Monitoring System for a Large Petrochemicals Manufacturer

Business Objective

Remotely monitor real-time health of the various systems in the plant

Key Solution

  • Built a virtual plant as a digital replica of the real plant
  • Enabled monitoring of plant health in real-time with key KPIs, equipment condition and parameters operating range
  • Detailed monitoring of all the systems within the plant – feedstock, cracking, storage, polymerization, bagging, utilities etc.
  • The solution diagnosed the problem of equipment with bad health or those operating at off-limit parameters; identified the root cause and recommended actions, enabling the operator to take quick and valuable plant floor level decisions

Business Impacts & Outcomes

  • Improved production and yield
  • Reduced energy consumption
  • Improved uptime of plant and assets
  • Maximized operational life of plant assets

Business Impacts & Outcomes:

  • Improved production and yield
  • Reduced energy consumption
  • Improved uptime of plant and assets
  • Maximized operational life of plant assets