The scheduling of production orders is one of the most frequently encountered problems in a manufacturing environment. Good scheduling algorithms can avoid many problems which limit the output of production your production process.
Some frequently encountered issues are listed below, but it is important to keep in mind that every production process is unique. Hence, a dedicated approach which is tailored to the specifics of the production procedure as well as a company’s economic goals can greatly improve the performance of a process.
Selecting the right production location
Larger companies often use geographically dispersed production locations. In such cases optimising the production schedule in all local plants is unlikely to reduce in a group-wide optimal solution. The ideal solution should take into account important facets such as client production costs, lead time, transportation costs as well as production capabilities at the various production locations.
Avoid needless waiting for machine operators
In many production environments the number of machines exceeds the number of operators. This situations is likely to lead to situations where one or more machines is standing idle waiting for an operator. Good scheduling practices can avoid these situations by creating a cadence which ensures that the number of idle machines never exceeds the available number of operators.
Losses due to excessive changeover time
In many production processes the time needed to switch from one product to another product influences the changeover time needed to get the machine ready for production. Choosing the right sequence of activities can significantly increase the output of the machines.
And many other challenges…
This list of potential scheduling issues could be extended almost indefinitely. Especially because many problems are highly specific to the production environment. Moreover, scheduling problems are not limited to production environments but are also one of the key difficulties when managing projects, filling out staffing rosters and most other operational tasks associated to doing business.
Kerkhove, L.P. and Vanhoucke, M., 2014, “Scheduling of unrelated parallel machines with limited server availability on multiple production locations: a case study in knitted fabrics”, International Journal of Production Research, 52, 2630–265. (link)