This paper considers a single machine scheduling problem where the machine is shared by multiple sub-production systems. Each sub-production systems has heterogeneous local objectives (e.g., minimization of total completion time, maximum tardiness and makespan). In a distributed manufacturing environment, no sub-production system has complete information (e.g., processing time, due date) of the entire system. This paper provides a distributed scheduling method to find close-to-optimal coordination on the shared machine using minimum local information sharing among sub-production systems. The proposed method is compared to pareto solution that can be found in a centralized environment.