A majority of businesses today schedule their operations using simple rules which are often coded in Spreadsheet models. These essentially sort jobs by their due dates / priority and assign machines to jobs serially. This provides inferior (and sometimes infeasible) results. Instead, the solver technology allows for solving the scheduling problem in a holistic manner – where the schedule is optimal and always feasible.
Matching jobs to workcenters seems like a simple job, but it isn’t. Jobs have due dates, earliest / latest start times, dependencies, priorities, special processing requirements, etc. The workcenters have setup times, downtimes, changeovers, cleanups, etc. When there are many jobs and workcenters, scheduling becomes very complex. Modern mathematical and constraint programming software enables solving such scheduling problems with far more superior results than what can be done by simply using rules-based approaches.
Due date adherence for jobs
Line-dependent variable job durations
Hard and soft dependencies between jobs
Support ASAP and JIT modes
Honor line downtimes
Honor manpower limitations
Schedule mid-week equipment cleanup
Setup times for lines
Split / parallel jobs
Handle fixed jobs and overrides
Powered by MIP / CP solvers
Handle work in progress (WIP)
Available as a service – can be called by a client
Integrated with a relational DB
What-if scenario analysis capability
Step-wise optimization to handle prioritized mutiple goals
Intuitive User Interface
Rich Gantt chart
Tables and canned reports
Can be interfaced to ERP
Can upload/download data using Excel
Systematic input data error trapping
Infeasibility analysis and reporting
Traffic lighting to efficiently manage workflow
A crude oil refinery is like a massive freight train – it cannot be stopped or slowed down easily. Hence the ships serving a refinery have to be scheduled over a horizon of months. Today’s tools use rules of thumb to approximately schedule shipments of crude oil parcels and often without regard to critical logistical constraints like tidal windows, berth availability, etc. This results in costly demurrage expenses and blending expenses.
In the cellar operation, blending and filtering of wine in undertaken among many other operations. This is a resource intensive operation. BOLT was used to optimally schedule tanks and filters in a 7 day horizon with excellent results. The tank headspace savings were on the order of 10% and the filter scheduling ensured minimal changeovers. The savings were on the order of $5 Million in capital avoidance by using BOLT.