Lead-time variability

Lead time variability measures the variability in lead time. 

Supplier variability Supplier lead time variability, yield. 

Y. Lu, J.-S. Song, and D.D. Yao. Order fill rate, lead time variability, and advance demand information in an assemble-to-order system. Working Paper, 2001. Columbia University, http //www.ieor.columbia.edu/ yao/lsy 1 rev 1 b.pdf... 

Buffer stock = f(service level, lead time variability, demand variability) Figure 6.3 When the reorder point... 

A buffer (or safety) stock line is shown below the reorder level. Buffer stock acts as a safety net in order to cushion the effects of variability in demand and in lead times. Buffer stock is a function of the service level (risk of stock outs), lead time variability and demand variability. The re-order point is therefore the sum of the forecast demand during the lead time plus the buffer stock requirement. There are various ways of calculating buffer stock (for a detailed coverage, and for details of EBQ and EOQ calculations, see Vollman et al. 2005, and Waters, 2003). 

The preceding example emphasizes the impact of lead lime variability on safety inventory requirements (and thus material flow time) and the large potential benefits from reducing lead time variability or improving on-time deliveries. Often, safety inventory calculations in practice do not include any measure of supply uncertainty, resulting in levels that may be lower than required. This hurts product availability. 

Identify factors that influence the required level of safety inventory. Safety inventory is influenced by demand uncertainty, replenishment lead times, lead time variability, and desired product availability. As any one of them increases, the required safety inventory also increases. The required safety inventory is also influenced by the inventory policy implemented. Continuous review policies require less safety inventory than periodic review policies. 

Since demand and lead time are never certain, there is a need for safety stock. Safety stock reduces the likelihood of a stock-out. Safety stock is the amount of stock that is held in excess of expected demand and expected lead time due to variable demand and variable lead time. Lead time is time between submitting a purchase order and receiving the purchased items. Lead time, of course, can and does fluctuate. Lead-time variability is the byproduct of ... 

Dirac s theory therefore leads to a Hamiltonian linear in the space and time variables, but with coefficients that do not commute. It turns out that these coefficients can be represented as 4 x 4 matrices, related in turn to the well-known Pauli spin matrices. I have focused on electrons in the discussion it can be shown... 

There are several sources of irreproducibility in kinetics experimentation, but two of the most common are individual error and unsuspected contamination of the materials or reaction vessel used in the experiments. An individual may use the wrong reagent, record an instrument reading improperly, make a manipulative error in the use of the apparatus, or plot a point incorrectly on a graph. Any of these mistakes can lead to an erroneous rate constant. The probability of an individual s repeating the same error in two successive independent experiments is small. Consequently, every effort should be made to make sure that the runs are truly independent, by starting with fresh samples, weighing these out individually, etc. Since trace impurity effects also have a tendency to be time-variable, it is wise to check for reproducibility, not only between runs over short time spans, but also between runs performed weeks or months apart. 

Another perspective for production simulation is automatic capacity utilization optimization of multi-product systems. As discussed, this task may be very difficult because of the many different variables and boundary conditions. In an environment integrating optimization and simulation, the optimizer systematically varies the important decision variables in an external loop while the simulation model carries out production planning with the specified variables in the internal loop (see Gunther and Yang [3]). The target function, for example total costs or lead times, can be selected as required. The result of optimization is a detailed proposal for the sequence of the placed orders. 

The relaxation variables focus on the front-end of the value chain in sales and distribution excluding production and procurement due to the commodity value chain characteristics with long production lead times and less flexibility in the backend. Of course, it is possible to have relaxation variables for all constraints and areas of the value chain. However, this would lead to higher complexity for the planner as well as longer solution times with more integer variables. Therefore, relaxation is kept limited. 

The analysis is the same as in the preceding section, as long as the relationship between potential and time has not been introduced. The same dimensionless approach may also be followed with the exception of the time variable, which may now be normalized against the inversion time tR t = t/tR, leading to the following definition of the normalized current A = /FSC ) [D. In applying equations (6.1) to the first potential step,... 

The disappearance of the time variable s in front of 1 corresponds to establishment of the steady state discussed in Section 2.2.1, leading to... 

Speed and improved quahty are also important. In the analysis of quinizarin in gas oil, transfer to the automatic regime immediately improved performance. Manual solvent extraction is a very boring task. An analyst, in an attempt to relieve the monotony, will set up a series of extractions in parallel. However, the sodium salt of the quinizarin is an unstable complex. Inevitably, variable times are taken for the solvent extraction, which leads to variable product development and imprecise results. Automation accurately sets the time for the extraction, removes this area of variability and provides consistent and rehable results. 

When an excipient distributor is sourcing a material for a user for the first time or even for subsequent orders on a nonstock item, a key element of information that must be communicated to the user is the availability of the excipient and the time it will take between when an order is placed and when the excipient is actually delivered to the user site. The definition of availability can be variable, especially if the distributor happens to represent international excipient makers, who may have the material in stock overseas, requiring additional lead times of anywhere from two to eight weeks, depending on the service of the supplier and customs, and, now as a result of the Bioterrorism Act, FDA intervention with entry into the United States. 

Next, the argument is that, for not too slow charge transfer, the rate of change of cD (0, ) and cR (0, ) with the auxiliary time variable is much less than the rate of change of (t — u) m. The concentration term, c — c(0, u), can then be considered as a constant in the integration, which allows the integration to be performed, leading to... 

The measurement of recovery is intended to be a measure of the elastic component of softness but it is rather debatable whether the strain rates and recovery times in the ISO and ASTM procedure yield results relevant to processing conditions. Recovery at room temperature as in procedure A of ASTM must be liable to lead to variable results. 

When designing plastic parts it is often recommended that the part have uniform thickness. This is especially true for semi-crystalline polymers where thickness variations lead to variable cooling times, and those in turn to variations in the degree of crystallinity in the final part. Variations in crystallinity result in shrinkage variations, which lead to warpage. However, it is often necessary to design parts in which a thickness variation is inevitable, i.e., extrusion profiles with thickness variations as shown in Fig. 6.14. 

Pharmacokinetics (PK) can be a major source of variability in the dose response relationship. It manifests itself in interindividual differences in the plasma concentration-time profile of a drug. Factors which lead to variability in the ADME parameters are therefore of importance in understanding overall variability in PK. 

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