As an emerging trend in manufacturing systems, Cloud Manufacturing provides the platform to explore the framework of optimization models with ubiquitous access to machine data. The dimensions of machine data such as availability, efficiency, capacity and health status are explored to study the problems of capacity reservation, integrated maintenance & scheduling and logistics for discrete manufacturing firms.

The problem of integrated maintenance & scheduling is studied in the setting of a single machine where the decision maker owns the facility. The machine has a demand of jobs that have a standard processing time, and the actual execution time of any job depends on the "running" state of the machine. Pre-emptive maintenance (PM) is done on the machine to keep the execution time of the job to its minimum by bringing the machine to the "as-good-as-new" state. The PM activity can be done only after completion of a job and the jobs cannot be interrupted while they are being processed. The tardiness of the schedule can be brought down by improving the processing times of the scheduled jobs through selective preemptive maintenance activities. Further, energy cost in the schedule is incurred based on total machining time and the objective of the problem is to minimize the total cost that includes tardiness cost, maintenance cost, and energy cost for the overall schedule. The model is formulated to understand the impact of introducing maintenance activities on the job processing times and subsequently the tardiness as well as the energy costs through the production schedule.

Capacity reservation problem is studied from the perspective of a manufacturer who needs to outsource the production orders to prospective suppliers. The suppliers have different process capability levels and offer a contract in accordance with their performance abilities. The premium supplier offers an option to reserve capacity before the beginning of the planning period. The manufacturer who faces stochastic demand must decide upon a reservation policy and choose to either reserve capacity with the premium supplier or go for the spot market. A supplier is eligible only when the requirement of all processes is met with the facilities available. The price for the spot market is a function of the realized demand and the premium for having reserved capacity. The objective of the manufacturer is to minimize the overall outsourcing cost that includes scenarios of with and without reservation. The problem is looked at in terms of dual sourcing with the two suppliers offering different contract parameters.

The execution of outsourced orders is further explored with the inclusion of logistics involved in shipping the finished goods to the manufacturer’s warehouse. The suppliers’ warehouses are in distant hubs and belong to the suppliers chosen to execute the production orders. The shipments to manufacturer also account for the delayed deliveries and environmental costs. The objective in this case includes the transportation economics for the chosen supply chain network.