Term
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Definition
A managerial statement of time-phased production rates, work-force levels, and inventory investment, which takes into account customer requirements and capacity limitations
This is the plan with the longest time horizon. Again, the actual length of the horizon, and the size of the “time buckets” it is divided into will vary depending on the nature of your business. An industry with rapid new product development and high variability will typically have a shorter horizon with short time buckets. |
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Term
| Master Production Scheduling |
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Definition
The master schedule is the first level of disaggregation of the aggregate plan. It is here that we begin to “break down” the “products” into more real end product items
The time factor is also usually different. Typically, the master production schedule (MPS) is of a shorter time horizon (under no circumstances is it longer) than the aggregate production plan (APP), and uses finer time buckets. |
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Term
| Three Variations of MPS/APP |
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Definition
Chase, Level, Stable Workforce
One can adopt a “chase” strategy and allow production and manpower to fluctuate to perfectly match demand (and thus maintain no inventory), or one can follow a “level” strategy, and maintain a constant production/workforce level, allowing changes in inventory to buffer you from the changes in demand level, or one can follow a “stable workforce” plan by allowing variable working hours to to buffer against variation. |
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Term
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Definition
| inventory which has not yet undergone any transformation by the company. Raw materials can be highly processed parts (e.g. circuit boards), just so long as all processing was performed outside of the operational unit in question. |
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Term
| Work In Process Inventory |
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Definition
| inventory which has already undergone some transformation by the operational unit, but is not yet completed. |
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Term
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Definition
| - inventory which has been undergone all transformations to be performed at the operational unit, and which is therefore ready to be passed on to the customer. |
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Term
| Safety Stock Inventory (Reason For holding) |
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Definition
| inventory which is being held to buffer against some form of uncertainty. Typical uncertainties are the amount of demand or the supply of the product. |
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Term
| Cycle Stock (Reasons for holding inventory) |
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Definition
| inventory that is held because the supply/source of product is not continuous. This can occur for a number of reasons. One common reason is because the process involved requires batching (e.g. a biochemical process) or because some resource required must be shared with more than one product (e.g. a plastic injection molding). Another reason is that it simply may not be economically efficient to produce the product continuously, and so we choose to produce in batches. |
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Term
| Pipeline Stock (reasons for holding) |
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Definition
| inventory that is located somewhere in the production or delivery process (“in the pipeline”). |
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Term
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Definition
| inventory that is held to buffer against seasonality in demand (this differs from safety stock which is used to buffer against uncertainty). |
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Term
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Definition
Number of units - an absolute measure/physical count. This is something that should always be known , and yet is not very useful from an evaluative standpoint.
Dollar value of units - a cost measure. Simply multiply the number of units held in inventory by their value. The choice of value (cost of product or sales value) depends on the context in which the measure is to be used.
Weeks of supply - a relative volume measure. Divide the number of units of inventory by the weekly demand rate. This is the inventory equivalent of ROI.
Inventory turns - another relative measure. Divide the annual sales volume by the number of units of inventory. Note that this is the inverse of the “years of supply” measure. |
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Term
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Definition
| the amount of inventory ordered is fixed a predetermined level, Q. This quantity Q is ordered when the inventory position falls to a predetermined reorder level, R. |
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Term
| Assumptions for the Basic FOQ Model |
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Definition
1) the demand for an item is constant,
2) the item is produced or purchased in lots,
3) decisions for one item are not affected by decisions for another,
4) there is no uncertainty for demand or supply
5) replenishment is instantaneous, and
6) holding, setup, and purchasing costs are the only relevant costs. |
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Term
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Definition
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Term
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Definition
| the amount to order. “Each time they place an order, the company purchases 200 widgets”. “The order quantity is 300 televisions.” |
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Term
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Definition
| the demand rate - usually per year, but not necessarily. “The company sells 20,000 widgets per year”. |
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Term
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Definition
| the cost per setup or order. “Each time the company places an order, they incur a $50 charge.” “Ordering cost is $45 per order.” |
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Term
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Definition
| the cost to hold a single unit in inventory for a fixed period of time. “Each unit costs $7.50 to hold in storage for one year”. “Holding costs are $2 per unit per month.” “It costs $12 each year to hold a copy of the study guide.” |
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Term
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Definition
| the per unit holding cost, expressed as a percentage of the cost of the item. “Each unit costs 25% of the cost to store in inventory for one year.” “The annual holding cost per widget is 25% of its price.” |
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Term
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Definition
| the cost of the item. “Each widget costs $30". |
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Term
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Definition
| the production rate or the delivery rate of an item. If this is not mentioned, then P is infinite (instantaneous replenishment) and P/(P-D) is 1. If it is mentioned, then you must use P in the P/(P-D) term. “The company has its own manufacturing facility in which it produces carpet at the rate of 150 yards per day.” “The bears are supplied at a rate of 800 per day.” “The supplier can deliver product at the rate of 200 units per day.” |
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Term
| Garvin 8 Dimensions To quality |
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Definition
1. Performance. The product’s primary operating characteristics.
2. Features. Supplements to a product’s basic function - the “bells and whistles”.
3. Reliability. The time until a product malfunctions and needs repair.
4. Durability. The time until a product needs replacement.
5. Conformance. The degree to which a product conforms to established standards.
6. Serviceability. The ease of maintaining and repairing a product.
7. Aesthetics. Overall appearance/appeal - how it looks, feels, sounds, tastes, or smells.
8. Perceived Quality. Customer’s perceptions of a product, based on inferences from reputation, brand image, advertising, marketing approach, packaging, etc. |
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Term
| 4 Costs associated with Quality |
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Definition
Prevention
Appraisal
Internal failure
External Failure |
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Term
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Definition
| These are the costs associated with improving the quality of the product. Issues such as worker training, design for quality/manufacturability, supplier certification, maintenance, etc. all contribute to this. |
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Term
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Definition
| These are the costs of evaluating the level of quality. Inspecting incoming materials, testing finished products, and quality audits are all examples. |
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Term
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Definition
| This is the cost incurred when the product or process fails before it reaches the customer. Defective material scrap, rework, and machine repair are all examples. |
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Term
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Definition
| This is the cost incurred when the product fails once it reaches the customer. Warranty costs, field maintenance and repair, loss of customer good will and reputation, and product liabilities are all examples. |
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Term
| The two Quality Relationships |
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Definition
| First, the closer a failure occurs to the customer, the more expensive it is. Second, the farther removed from its source that a quality problem is discovered, the more expensive it is. |
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Term
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Definition
By this Crosby means that the expenditures to improve quality (i.e. additional prevention) typically are less than the savings returned in the form of fewer failures.
From the graph in class, the overall total expenditures decreased. However, this decrease was not reflected evenly across all the different categories. Note that this overall decrease was accomplished by an increase in the prevention costs. |
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Term
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Definition
3. Cease dependence on inspection to achieve quality.
4. End the practice of awarding business to the lowest bidder. Instead, reduce cost by reducing variation.
6. Institute training on the job.
8. Drive out fear. “I would never want to work for someone I could not argue with, and respect.”
10. Eliminate slogans, exhortations, and targets. Wrong emphasis as to who is most responsible.
12. Remove barriers to pride of workmanship. |
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Term
| Deming's main points on Quality (2) |
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Definition
You can not inspect quality into a product or service, quality is built into a product or service
Many Defects are not found through inspection, it is not fool proof! |
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Term
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Definition
| The Baldrige Award is America’s highest award for quality, established by President Reagan in 1987. It is similar in many ways to the Deming award of Japan. Firms apply for the award and undergo an extensive examination. A firm applies to one of six categories: manufacturing , service, or small business, education, health care and not-for-profits. |
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Term
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Definition
In contrast to the Baldrige Award, ISO 9000 is a certification program that does not limit the number of firms that can be recognized. It is much less broad in its focus than the Baldrige, focusing mainly upon the extent to which procedures are documented, consistently performed, and suited to the task at hand. Unlike the Baldrige award, which is externally focused on customer satisfaction and strategic positioning, ISO 9000 is internally focused on processes.
The biggest driver that is pushing firms to apply for ISO 9000 certification is the fact that it is rapidly becoming the standard that is required to do business in the European Community. |
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Term
| The Magnificent Seven (Tools for quality Improvement/Continuous Improvment) |
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Definition
Process Flow Charts
Cause and Effect Diagram (Ishikawa or Fishbone)
Control Charts
Histograms
Check Sheet
Pareto Charts
Scatter Diagrams |
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Term
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Definition
| all assignable causes of variation have been weeded out of the process and only fluctuations due to environmental factors remain. They can not be traced back to a single cause. These fluctuations should appear random, and follow historical patterns (w.r.t. mean and standard deviations) |
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Term
| The three components of Control Charts |
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Definition
| some measure of the central tendency (the average) for Y, the upper control limit (the point for which Y from an in control process is highly likely to fall below), and the lower control limit (the point for which Y from an in control process is highly likely to fall above). The vertical axis of the chart is calibrated in units of Y and the horizontal axis is calibrated in units of time or sample sequence. |
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Term
| The rationale behind the statistical controls methods 6 sigma orientation |
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Definition
| The decision on whether to adjust the process has now been given a consistent, firm, rationale method. This will lead to better decision making. Excessive “tweaking” of the machinery (making adjustments when none are needed) leads to an increase in process variance and therefore a decrease in process quality. |
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Term
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Definition
| purpose of the control chart is to give us an objective, statistically based tool to judge if a process is in control or out of control. |
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Term
| Statistical Control and the two hypothesis |
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Definition
H0: The system is in control.
H1: The system is out of control.
The idea of hypothesis testing is that we examine the data and see if the null hypothesis (H0) is tenable. If so, then we would not reject the null hypothesis in favor of the alternate hypothesis (H1). If, however, the data was not consistent with the null hypothesis, then we reject it in favor of the alternate |
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Term
| Is a process out of control? We look for these tell tale signs |
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Definition
• A single sample statistic that is outside of the control limits (since the custom is control limits that are plus and minus 3 standard deviations wide, they represent 99+% control limits).
• Two consecutive sample statistics near the control limits (recall that the majority of points should lie near the central line).
• Five consecutive points above or below the central line (what are the odds of getting five consecutive heads or five consecutive tails when tossing a coin?).
• A trend of five consecutive points.
• Very erratic behavior (e.g. several large swings or insufficient number of points near the central line). |
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Term
| Producers Risk (false Positive) |
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Definition
| With a normally functioning system in control, and a width of plus or minus 3 standard deviations, it is natural and expected that 1% of all samples statistics will fall outside the control limit boundaries as a function of normal, random variation. This is called type I error (a false positive), or producer's risk. The wider the control limits, the less the probability of committing type I error. |
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Term
| Consumers Risk (False Negative) |
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Definition
System is out of control but we believe it is in control This is a type II error and also called a consumer risk
Type II error is difficult to compute. How big to set control limit width is a crucial decision, and the cost and sensitivity to type I and type II errors is a key issue.
Since it is difficult to impossible to assess type II error directly, we usually think in terms of type I error, and set our control limit widths accordingly. |
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Term
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Definition
| The R-chart works off of the sample range (the difference between the highest and lowest single observation). While the range of a sample is not the variance, it is an acceptable proxy, and it is much easier to compute. |
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Term
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Definition
| We refer to these as the specification limits (different from the control limits). Any observation outside those limits would be classed as defective, while anything within those would be considered non-defective. We therefore turn our sample observations into a stream of 0s and 1s, with 1s representing each defective observation. We can then calculate our necessary parameters for each control chart. These calculations are quite easy, with p equal to the percent defective in a given sample |
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Term
| THE Relationship between increasing Z Scores and Type 1 and Type 2 errors |
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Definition
| What is the result of this tinkering with z? If you recall our discussion of type I and type II errors you should realize that as z increases, the likelihood of committing a type I error has decreased while the likelihood of committing a type II error has increased. Type II error is difficult to determine exactly, mainly because it requires knowledge of a number of factors, some of which we don’t know exactly. Type I error is easy to assess, however, because it is based primarily on the null hypothesis, which is that the system is in control and all deviations from the mean are due to random chance. We therefore often specify z based on the level of type I error we are willing to live with. |
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Term
| The relationship between Sigma and Type 1 and Type 2 errors |
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Definition
| 3 sigma minimizes the total of type 1 and type two errors! They behave oppositely with respect to the width of Z |
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Term
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Definition
The capability index (Cpk) shows how well the parts being produced fit into the range specified by the design limits. If the design limits are larger than the three sigma allowed in he process, then the mean of the process can be allowed to drift off-center before read¬justment, and a high percentage of good parts will still be produced.
Because the process mean can shift in either direction, the direction of shift and its distance from the design specification set the limit on the process capability. The direction of shift is toward the smaller number. |
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Term
| What we need to know about capability index (CPK) |
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Definition
The high the index the better! a number over 1 is typicaaly good, 2 signifies a highly acceptable process where the UTL LTL are in alignment with the upper and lower control limits of our data.
As standard deviation in the equation decreases the CPK increases and the process is leaner and taller around the center
As variation around the mean decreases and becomes more centered our CPK increases
Review notes to make sure you understand this process, only one question!
Variability costs money! |
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Term
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Definition
| Allows us to determine at what point we need to reorder our FOQ to avoid a stock out based on our Saftey levels, given on exam MAKE SURE YOUT UNITS WITH YOUR LEAD TIME ARE ALWAYS IN ACCORDANCE WITH DEMAND AND THE STANDARD DEVIATION IS CONVERTED PROPERLY! |
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