Supply Chain Management Overview the

CPM is critically important from a supply chain management standpoint in optimizing inventory positions by location throughout a distribution channel as well (Omar, 2009). All of these factors contribute to the automating of CPM and PERT through organizations who are heavily reliant on their supply chains to gain a competitive advantage. The optimization of inventory workflows using CPM and PERT contribute to that competitive advantage over time. PERT and CPM also can be used to measure the financial impact of these strategies over time as well. That is the future direction of ERP and Web Services in manufacturing specifically.

Services Scheduling

Services scheduling is difficult due to a variety of factors. First, services are by definition a commitment of future value delivered. Completing services may take an exceptionally longer period of time than anticipated and the act of providing a service is not a finite asset; it is rather the attainment of satisfaction with a customer (D Aquila, 1993). Scheduling services as a result is a difficult task. Second, services can vary in terms of their relative value over time, with the service provided for better management of a customer issue requiring escalation depending on the troubleshooting completed. Third, services are often sold with products in Business-to-Business (B2B) markets and as a result they are often bundled into the price of the product. This makes for a blended contribution margin and often a difficulty in separating each (D Aquila, 1993). When companies schedule services they often over-schedule them assuming customers will cancel their appointment. This is typically the case yet when an external event forces the need for service then customer responsiveness suffers.

How Expert Systems Improve Maintenance Systems

The development of expert systems that are rules- and constraint-based can be used for effectively managing maintenance systems by defining predictive relationships between components and anticipating when certain ones will need to be replaced.

The concept of Maintenance, Repair and Overhaul (MRO) in the aerospace and defense industries is a case in point. Expert systems are used for managing the preventative maintenance of jets and also for scheduling updates to tooling procedures, systems used for working on the planes and also troubleshooting tasks as well. As a result the development of expert systems to support maintenance systems is commonplace in specific industries already. These systems significantly reduce overall costs and support the development of self-regulating complex systems including the last generation of jets which have expert systems onboard to self-diagnose themselves.


The progression of MRP systems supporting the basic functions of a manufacturing company to the development of mathematical models that seek opt optimize demand and aggregate planning shows a progression towards using intelligence to gain greater efficiencies over time. The use of PERT and CPM techniques for managing complex projects has been proven in the decades of their use and have also contributed to the financial performance of firms using them. The bottom line is that as companies seek to become more demand-driven they move from an inward focus on MPR and reporting to seeking out strategies for being more demand-driven and in touch with the market. Once this is achieved these companies seek to optimize their internal process efficiencies through the concepts discussed in this paper.


Byrne, MD, & Jackson, RJ. (1994). A study of bottlenecks in a MRP environment using simulation. International Journal of Production Economics, 35(1-3), 115.

D Aquila, Nancy Welch. (1993). Facilitating inservice programs through PERT/CPM. Nursing Management, 24(5), 92.

SCH Leung, Y Wu, & KK Lai. (2006). A stochastic programming approach for multi-site aggregate production planning. The Journal of the Operational Research Society, 57(2), 123-132.

Omar, a.. (2009). Uncertainty in Project Scheduling – Its Use in PERT/CPM Conventional Techniques. Cost Engineering, 51(7), 30-34.


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