This study focuses on production scheduling problems in metal pipe manufacturing, where customer orders differ in terms of type, thickness, and quantity. Each order is considered a job with a processing time that varies based on the machines involved in the production process. To produce the next job, there is a setup time required that depends on the machine, which is assigned to, and the current job being processed on that machine which is referred to as a job- and machine-sequence-dependent setup time. Since it is not possible to obtain an optimal solution for a large scheduling problem by using the mathematical programming approach, a heuristic method is a preferable choice to handle this. Therefore, this paper aims to illustrate the application of heuristics that features dispatching rules to solve the aforementioned scheduling problem through a numerical example. These rules, which explicitly consider the job- and machine-dependent setup time include the shortest job completion time, shortest job completion time based on the longest processing time, and shortest job completion time based on the earliest due date, and shortest job completion based on the minimum slack. A comparison regarding the effectiveness of these rules is also conducted. The results show that the shortest job completion time based on the minimum slack yields the best performance concerning the makespan and the second-best performance in terms of total tardiness. In addition, the shortest job completion time based on the earliest due date produces the best performance for both total tardiness and the number of tardy jobs. This study focuses on production scheduling problems in metal pipe manufacturing, where customer orders differ in terms of type, thickness, and quantity. Each order is considered a job with a processing time that varies based on the machines involved in the production process. To produce the next job, there is a setup time required that depends on the machine, which is assigned to, and the current job being processed on that machine which is referred to as a job- and machine-sequence-dependent setup time. Since it is not possible to obtain an optimal solution for a large scheduling problem by using the mathematical programming approach, a heuristic method is a preferable choice to handle this. Therefore, this paper aims to illustrate the application of heuristics that features dispatching rules to solve the aforementioned scheduling problem through a numerical example. These rules, which explicitly consider the job- and machine-dependent setup time include the shortest job completion time, shortest job completion time based on the longest processing time, and shortest job completion time based on the earliest due date, and shortest job completion based on the minimum slack. A comparison regarding the effectiveness of these rules is also conducted. The results show that the shortest job completion time based on the minimum slack yields the best performance concerning the makespan and the second-best performance in terms of total tardiness. In addition, the shortest job completion time based on the earliest due date produces the best performance for both total tardiness and the number of tardy jobs.