Theory of Constraints Handbook - James Cox Iii [680]
The queue time or white noise is the time when no value-added or productive time is being realized. In other words, Fig. 35-5 is showing how the elapsed time is still being accumulated between the productive tasks while providing no value-added to the output of the organization. The accumulative effect of productive time plus queue is equal to the total cycle time. Therefore, it follows that for any organization to improve, any scheduling algorithm must be able to synchronize and leverage the availability of the resources in order to eliminate this excessive idle time to maximize the Throughput of the organization. This means that to increase Throughput, which was previously defined as sales minus TVC, the organization must accelerate the flow of work or, more precisely, the rate of work flow. That is, with a given amount of resources, the organization must be able to deliver the final product to the market sooner. This rate of workflow is the key to being more responsive to the customers and increasing the company’s profits.
FIGURE 35-5 Elements of task time for a dependent series of tasks.
The company must find ways of reducing the cycle time of producing and delivering its products. The easiest and most effective way is by reducing the queue time (Fig. 35-5) of resources waiting to be utilized, the principle reason WIP starts to increase, which leads to resources being significantly more productive (Little’s Law; Hopp and Spearman, 2000). There are different ways this can be accomplished but one fact is indisputable—every company is susceptible to variability; therefore, any successful solution must be able to better manage the uncertainties, changing of priorities, and schedule changes. This variability causes major impact to the work schedules, which become the single greatest contributor to the resource queue. There is a direct relationship between resource queue time and productivity. So if cycle time must be significantly reduced, any breakthrough scheduling algorithms must reduce variability when possible, thereby reducing queue times. This must be done while providing real-time information to managers to mitigate the increased risk of managing variability.
The uncertainty of resources, material availability, and required technical information, subjected to the effects of unforeseen common and special causes, can be expressed as variability. Lacking a deeper understanding of how the variability can be mitigated leads to many instances of companies actually using the wrong scheduling tool while attempting to better manage the variability. For example, they may be using only project management tools when this may not be the best scheduling algorithm because they view themselves as a “project management” company, when in reality different parts of the company may be subjected to different kinds or types of variability, which means more than one scheduling algorithms is required. Alternatively, they may only be using production planning and control scheduling tools because they view their company as a floor scheduling/manufacturing company. In addition, regardless of which tool they decide to use, in many cases they may decide to schedule and manage their material requirements by imbedding them in whatever work-scheduling tool they are using instead of using the appropriate material management algorithm.
Many of these mistakes can be traced to a lack of understanding of the origin and the cause and effect of the variability. In order to clarify this confusion, a further classification of