| dc.description.abstract | It is undeniable that preventive maintenance (PM) is extremely significant in industry
capital because of its direct relationship to manufacturing continuity. This research
aims to offer a practical automated system to assist in the preventive maintenance
planning process. A mixed integer-linear programming (MILP) model was created and
solved by CPLEX with a small dataset to give the best optimal solution. In addition,
Python code is also created based on Simulated annealing algorithm (SA) to deal with
big instances of data for shortening computation time while enduring the solution
quality. Practically, preventive maintenance planning becomes totally automatic as a
result of the use of a coding program, minimizing the risk of miscalculation, lowering
the time, and not needing a huge manpower to do. | en_US |
