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Enterprise resource planning (ERP) is an integrated management software for key business processes (Mesbahi et al., 2015), and it is used widely in supply chain management (SCM) where practices can be implemented jointly among supply chain partners so that they will remain competitive in a fast-changing business environment (Aggestam, 2016; Fernando & Evans, 2015). ERP software generally uses traditional material requirement planning (MRP) technique introduced by Orlicky in 1975 which allows the calculation for its production and purchasing planning modules. Traditional MRP assumes that manufacturing lead times are fixed constants (not dependent on production quantities) and that production capacities of all work centers are infinitely available (Jazouli et al., 2021). A master production schedule (MPS) is a key input that drives MRP calculations. Production and purchasing schedules are obtained after the MRP calculations are completed; however, due to the assumptions mentioned above, the production schedule may turn out to be infeasible in terms of capacity (i.e., the required capacity is more than available capacity) (Kanet & Stoblein, 2010; Teo et al., 2011). In such a case, a planner must either revise the MPS or the capacity level of post-MRP stage manually until the capacity becomes feasible (Permana et al., 2021). In practice, these manual revisions are time-consuming and complicated, and it is possible that the planner may not be able to achieve feasible capacity. This makes the use of traditional MRP logic in most ERP software a major disadvantage.
Many research studies have attempted to solve this disadvantage of the traditional MRP logic by developing a more advanced MRP logic called Finite Capacity MRP or the FCMRP system (Hill et al., 1997; Kim & Van Oyen, 2000; Pandey et al., 2000; Sum & Hill, 1993; Taal & Wortmann, 1997). Most FCMRP systems available in the literature are based on two basic assumptions: (1) that manufacturing lead times are not a fixed constant but dependent on production quantities, and (2) that all key work centers have finite capacities; the capacity used must not be greater than the available capacity. However, when the MPS has many orders competing for work centers, some orders may be completed later than their due dates.
Many research studies have attempted to solve this disadvantage of the traditional MRP logic by developing a more advanced MRP logic called Finite Capacity MRP or the FCMRP system (Hill et al., 1997; Kim & Van Oyen, 2000; Pandey et al., 2000; Sum & Hill, 1993; Taal & Wortmann, 1997). Most FCMRP systems available in the literature are based on two basic assumptions: (1) that manufacturing lead times are not a fixed constant but dependent on production quantities, and (2) that all key work centers have finite capacities; the capacity used must not be greater than the available capacity. However, when the MPS has many orders competing for work centers, some orders may be completed later than their due dates.