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  • Trim Optimization
  • Resource Allocation Models
  • Block Scheduling

  • Paper Machines
  • Rewinders
  • Extruders
  • Cutters/Sheeters
  • Carloading


  • Pre Trimtm Planning/Early Warning System
  • Micro Trimtm Production Scheduling
  • FloorTrimtm for Upset Conditions
  • Matrixsm for Small Mills


The focus of all Matrix products is to provide innovative systems, with the tools to help generate effective schedules in the "real world".

Case Studies

Detail mill scheduling is the point where customer orders meet manufacturing capabilities. Trim Optimization is the most discussed element; however, the entire mill process flow is in play when the paper machine schedules are generated. Some variables are more easily quantified than others, but not always more important. The focus of all Matrix products is to provide innovative systems, with the tools to help generate effective schedules in the "real world".

Below are Matrix's solutions to the following "real world" situations:

Case A:  Scheduler needs better tools to deal with the complex scheduling tradeoff's involved in today's business climate.
Solution:  32.  Created a new multi-thread model that automatically seeks the best solutions for each order set being scheduled. The system evaluates alternative schedules and then displays up to seven for the scheduler to select.
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Case B:  Order set size mix does not generate efficient schedules.
Solution:  decision assist.  This toolset can be added to any system, and facilitates managing the order set or modifying the patterns generated by the algorithms. Optional rolls can be added from future orders or inventory, overruns can be set by order by percentage, or the order set can be scheduled by segments and recombined. The manual patterns routines can move rolls, change patterns, delete patterns or add patterns using innovative graphic displays.
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Case C:  Very limited warehouse space and customers release loads from blanket orders. Customer rolls must be direct loaded.
Solution:  carloading.  This system uses an algorithm that optimizes trim efficiency and loading simultaneously.

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Case D:  One machine with a minimum speed differential between the paper machine and the winder.
Solution:  linernb.  This system incorporates a special purpose algorithm designed to significantly reduce setups.

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Case E: High cost product susceptible to off quality areas in master rolls.
Solution:  badspot.  This system re-trims the orders around the off quality area, and develops makeup patterns for the lost rolls. If there are customers who will accept the off quality condition; the system will re-trim with roll placement. This feature places the off quality customer rolls over the affected area.

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Case F:  Small mill with limited in-house technical support was concerned about continuing support.
Solution:  support.  Under our leasing program, system changes were covered, including on-site visits when required. We have been in business for 38 years and have always provided complete, cost effective support.

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Case G:  Include one roll from a blanket order in every pattern until the order is complete.
Solution:  32.  Created add-in module to insert a "plug" roll into every pattern.
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Case H:  Centralized scheduling for multiple mills with unique individual requirements.
Solution:  32.  Our system architecture, our library of algorithms, our special purpose add-in modules and our ability to "tailor" the user interface, make it easy for us to provide one system, which will fit all mills.

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Case I:  Printing customer wants all rolls assigned to separate loads by roll position in the pattern.
Solution:  32.  Created add-in module to perform load assignment by customer and roll position in the pattern.
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Case J:  A mills' customer specifies that their orders must come from a specific roll position in the pattern.
Solution:  32.  This system optionally forces roll placement to be a priority; if placement can't be achieved by post processing the schedule.
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Case K:  Roll size mix is changing and affecting scheduling effectiveness.
Solution:  32.  Created "learning database" subsystem to evaluate changes in size mix and reset the algorithm to maintain scheduling effectiveness.

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