Manufacturing customized products makes scheduling difficult. Since machine work scheduling influences net productivity, most industries focus on it. The number of machines and jobs to schedule increases the complexity of the challenge, emphasizing the need for an appropriate scheduling technique. Superior scheduling improves customer satisfaction, productivity, cost reduction, and competitiveness. This study addresses a flow shop scheduling problem that reduces tardiness by processing work via a sequence of machines. We need LINGO, an optimization modeling software, to address this. This method is effective and efficient. To demonstrate the proposed flow shop scheduling solution’s efficacy and efficiency, we must create 20 instances and solve with LINGO. For each instance, the result shows that optimum delay can be achieved from multiple job operation sequences. Additional research will include a sensitivity analysis to demonstrate the adaptability of the offered solutions and their results.