It is clear in today's global economy that manufacturers must excel in production if they want to compete successfully and survive. Better planning and scheduling systems are the keys to achieving this goal. Advances in computer and software technology should enable those systems to be much smarter than they used to be.

Rather than simply documenting transactions, the systems now have the capacity to analyze business situations and make decisions in support of corporate strategy and production objectives. The two primary aspects of the production planning and execution cycle, which are critical to achieving excellence and must be managed in an effective manner, are the production planning/scheduling phase and the production execution phase.

It is difficult to get these two distinctive steps to work together because they are so highly interrelated. One will not function if the other does not exist, is not properly implemented, or contains incorrect or outdated information.

The planning/scheduling phase should generate a detailed, realistic, synchronized, and optimized production schedule. The schedule should cover all resources used in production, go down to every level of the bill of materials or production operation, and be fully time-phased. The schedule should then drive the materials purchasing plan, which enables the company to fully benefit from the MRP concept as well.

Production schedules must accurately reflect what can be accomplished on the shop floor if they are to support efficient, uninterrupted production. There is no "correct" mathematical solution that will provide the perfect schedule. Rather, the schedule is a trade-off among solutions to production and cost constraints that vary from company to company.

Devising a schedule based primarily on theory and mathematical models, without considering the real day-to-day capabilities of the factory and internal constraints unique to the organization, will most likely be impossible to execute, requiring endless cycles of rescheduling to adjust to the "real" conditions on the shop floor. Those production changes and adjustments are very expensive (like an unnecessary change from one tool to another) and, therefore, should be minimized. Many hidden costs are typically not captured by the standard costing system, and as a result go unnoticed. But costs do affect the profit-and-loss picture.

Requirements for constant rescheduling are typically clear indications that the system is not reflecting the user's true manufacturing environment and customer order pattern. If market demand is changing rapidly, that doesn't necessarily mean the schedule must change constantly.

Rather, the schedule should consider the market pattern as one of its parameters, and find the best solution that would flatten the effect of peaks and valleys in demand on the production schedule, thereby smoothing the workload throughout the factory. This is where optimization algorithms click in.

The optimization process is a "higher," more value-added step. It takes the scheduling function further by comparing various realistic scheduling solutions to determine the best way to manufacture, giving the company additional productivity gains and savings. In fact, the optimization algorithms really enable a company to capitalize on the cost-savings properties of a good scheduling system apart from meeting customer demand on time.

In the modern manufacturing environment, all aspects of the operation must be considered in order to make good business and operational decisions. These factors should be declared to the system through a set of parameters. Values can be assigned to the parameters by the user. This arrangement gives the user flexibility in controlling the system's behaviour, since the parameters control the flow of the scheduling logic and decision making process.

The system should consider the parameters in accordance with its own priority level, as well as its relational effect on all other parameters. This makes the system very complex for the system developer, but practical, flexible, and easy for the end user.

Also, the operational knowledge available in the plant must be embedded in the system's logic and behaviour in order to implement an intelligent planning, scheduling, and execution system. This requires that the system vendor understand in detail the particular operation which is being computerized and the effect of all parameters on its decision-making process.

Experience shows that the payback on a scheduling and plant optimization system comes quickly, typically in several months. The system leverages the big investment the company has made in plant machinery and people by improving resource utilization and doing more with what it already has. MA