Equipment Schedule Optimizer (ESO)



In any processing or production environment optimal allocation of personnel to operations and processes is driven by the "equipment operating" schedules. After years of research on how to create optimized "equipment operating" schedules, Planmatics' team of academic experts, software engineers and business analysts developed the Equipment Schedule Optimizer (ESO) that works as a front end to Planmatics' LSS.


Planmatics' Equipment Schedule Optimizer (ESO) is a web-enabled solution for maximizing machine utilization within a material flow-through facility which has critical dispatch times - like in a just-in-time logistical system. The USPS sorting centers have such an environment. Thereby scheduling equipment against a volume arrival profile, ESO effectively minimizes machine run times, labor-staffing requirements, and overall idle time.


ESO is developed for postal organizations as a solution to a major problem faced by the postal facility managers: development of daily schedules for the equipment used to process varying mail volumes, while meeting critical clearance times. ESO helps to reduce the facility operating costs, and increase overall efficiency while generating an equipment schedule that is in line with organizational goals.


ESO considers volume arrival profiles on a half-hour basis, seven days a week. ESO demonstrates optimal flexibility by allowing managers to control multiple operating parameters such as equipment profiles, delivery cut-off times, start-up and shut-down windows for equipment, and multiple constraints on mail flow throughout the facility. The main objectives to be achieved through the use of ESO are


  1. Minimize left over volume
  2. Minimize Number of shifts
  3. Minimize Number of Setups
  4. Minimize Early Start Ups
  5. Minimize Number of Machines

This innovative modeling technique serves as an optimum front-end for Planmatics' Labor Schedule Optimizer System. By optimizing equipment utilization over sequential objectives of runtime compression, switching machines on and off etc., subsequent staff allocations are minimized.