, pronounced X-bar. A bar over any variable symbolizes an average value for that
variable. A double or triple bar symbolizes the grand mean or average of several averages.
Useful when using an interval or ratio scale.
TQM and Statistical Tools Glossary
ABC - Activity-based accounting - aimed at providing the true cost of each product/service and the elements which drive the process/service. ABC aims to provide for the management and quality needs of an organization - not just the financial accounting requirements. Traditionally, cost accounting assumes that products consume resources. Therefore, something not directly seen as a resource (for example, electricity, safety, bookkeeping) is viewed as an overhead cost and partitioned among products or services in some manner. In ABC, products/services are assumed to consume activities and activities consume resources. Process value analysis (PVA) is used to determine the cost of each activity. Ideally, in ABC there are no overhead costs; every product or service is the result of consumed activities and every activity consumes resources whose cost is known. The advantages of ABC are that the true cost of products and processes can be determined and expensive and/or non-value-adding processes can be identified.
Accuracy - the closeness between a true value and a measurement (or average of measurements). If the part really weighs 2.2 grams but the scale says 2.1 grams, the scale is inaccurate. If someone shoots at a target with a shotgun and on the average the distance from each pellet to the center of the target balances out, the shoot was accurate.
Allowance - the minimum clearance or maximum interference between two mating parts, i.e., both parts are at their maximum material condition. For example: a shaft at its upper tolerance limit and a hole at its lower tolerance limit. The result could be a clearance or interference fit depending on the tolerance limits.
AQL - acceptable quality level - the maximum percent nonconforming. AQL does not guarantee that every lot will have a certain maximum percent of nonconforming. The AQL does indicate the level of nonconformities that is satisfactory as a process average. (To avoid excessive rejected lots, the actual process average should be better than the AQL.) When a supplier utilizes a given AQL, the consumer (inspecting incoming product/materials/etc. and using the same or larger AQL) will accept the vast majority of lots produced.
Attribute - a qualitative characteristic that can be counted and/or a characteristic that an item/unit/batch/lot can be said to exhibit or not to exhibit. For example, cracks, blemishes, discolorations, knots, etc. could be attributes.
Benchmarking - identifying and adopting best practices. It is important to focus on practices, procedures, and processes - not products. For example, an automobile manufacturer has to pay vendors as does a restaurant. If the restaurant has the best vendor paying system, then the auto manufacturer should adopt the restaurant's procedure to pay vendors.
Binomial Distribution - a distribution of a dichotomous (either/or) values. Useful in SPC when parts are to be judged conforming or nonconforming, accepted or rejected. A p-chart, which looks at the proportion of defective or nonconforming parts, assumes the data is represented by the binomial distribution.
CANBAN - "sign board" in Japanese - a technique for routing and requesting parts used in pull and JIT systems. The canban is similar to a traditional material/part request or routing slip. However, the canban is attached directly to the container (ideally a modular system) which holds the lot of items (ideally a lot of 1). A latter process pulls its needed components directly from the container. When the container is emptied it is returned to the preceding process to be restocked. A preceding process only makes parts when it has a container (with canban) to fill. The canban typically includes: part number and description, processing codes/information, the name/location of the latter/pulling process, the name/location of the preceding/giving process, and an area to tally the number of lots filled and record the time lots were filled/pulled.
CE - concurrent engineering - a team approach to design and manufacture of a product. Traditionally, marketing has given engineering the specs for a product (hopefully with customer input), engineering would give manufacturing the plans for the product, manufacturing would set up the production technique, and labor would make the product. Debugging the design and the production technique was common. If each step is off a little, the compounding error produces a result not to the customer's expectation. Concurrent engineering addresses two primary problems: it delivers the quality the customer expects and it decreases the amount of debugging, design changes, and production changes that are necessary. It does this by utilizing teams at each of the quality function deployment stages. The teams would contain customers, vendors, and personnel from marketing, product design and engineering, manufacturing design, manufacturing labor, management, QC/QA, purchasing, shipping, and others. It is most important to get the maximum amount of input at the design stage. Teams at different QFD steps will vary as to their composition. For example: at the design stage there is likely to be more design engineers on the team than members from purchasing. However, every function involved at any QFD step is involved at every step. It is important that team members stay with a project through all of the stages, for example: it would not be advisable to Joe from purchasing take part in step one, Nancy from purchasing in step two, etc. Typically, the design stage is the longest step and increases the design time over traditional linear methods. However, the total time to deliver a debugged product to the consumer's liking is lessened. CE requires: use of TQM, QFD, teams, and DOE.
Characteristic - a feature, trait, or property of a thing that can vary and that all items in the population or sample possess to some degree. Therefore, characteristics help differentiate items. Characteristics can have constant or variable values. For example, all humans normally have eyes. Eye is the characteristic. The quantity value is a constant. The color value varies. In SPCit is most useful when characteristics, especially quality characteristics are observable and measurable. Color, weight, smoothness, length, beauty, hardness, etc. may be a characteristic.
Constant - quantity, feature, etc. that does not vary.
Consumer's risk - type II error - - the probability of making the false decision that a lot of product is conforming when actually it is nonconforming, likewise, the probability of finding that a process is in control when it really is not. The probability of making a Type II error is dependant upon the sample size, the producer's risk, and the sensitivity of measurement. The probability of making a Type II error decreases as the sample size increases, the producer's risk increases, or the desired sensitivity decreases. Consumer risk probabilities can be calculated or they can be interpreted from graphs called operating characteristic curves.
Continuous - a scale that contains continuous values, for example: 1.2 inches, 1.275 inches, etc.
Control chart - plots a statistic such as a mean, variance, or proportion over time. The value of the plotted statistic is compared to tolerance and control limits. Where the plotted points lie and the pattern they created tells us if the process in control or not (being affected by random or attributable error). Tolerance limits are set by design and originate with customer requirements. Control limits are based on the process's capability. To be able to correct a process that is out of control, the control limits must be within the tolerance limits. However, if control limits are too close to the target value/center line, there will be needless adjustment to an in-control process.
Defect - A departure of a quality characteristic from its intended level that causes the product or service not to satisfy user requirements (quality of perception). Defect and nonconformity are often used interchangeably, however, they are not synonymous. A defect implies a less than perfect condition; a nonconformity implies a reject.
Discreet - having identifiable measurement points, measured by whole integers, for example: Five bad parts. Attributes are most often measured discreetly.
Distribution - plot of values. Usually displayed as a histogram with the values of the parameteror statistic on the horizontal axis and their frequency or probability of occurrence on the vertical axis. Distributions can be continuous, i.e., infinite increments exist. For example, temperature could be 75, 75.2, 75.371, etc. Distributions can be discrete, i.e., the measurements can only be in whole units. For example, a part or a lot cannot have 1.5 defects; it has to have 0, 1, 2, etc. Several naturally occurring distributions can be mathematically modeled. This is fortunate because properties of the distribution, e.g., average value, spread in values, and shape, can be expressed in standard ways. Knowing the properties of a distribution is necessary for determining the probability of a certain value occurring or not occurring, the proportion or quantity of values above or below a certain point, and the probability that a sample statistic is the same or different from its associated population parameter. Three distributions useful in SPCinclude the binomial, normal, and Poisson distributions.
DOE - design of experiments. Refers to statistical methods to predict the optimum combination of parameter values. Optimum refers to the highest quality at the lowest cost. Usually, the most robust design is sought. Parameters are the inputs to the process. Design refers to the statistical method and experimental designs utilized, most often, an analysis of variance model. Experiment refers to the situation that an experiment is being conducted. The experiment can take place before full-scale production to determine initial parameter values, or during production to fine-tune values. For example: assume the parameters and associated values of carbon content (.008%, .009%, .01%), temperature (1400, 1500, 1600), time in oven (40 min., 45 min., 50 min.), and quenching medium (oil, water, brine). To test every one of these combinations to find the best one would take 34 (81) trials. Experimental designs exist to find the best combination of parameter values using only a few trials.
Error - any deviation from the target or true value. Usually broken down into two components: 1) random/normal/natural error that is to be expected and cannot be decreased and 2) assignable/attributable error that can be controlled. Decreasing assignable error is at the heart of QC. Statistical inference involves making decisions about a population (lot, batch, etc.) from investigating a sample of the population. Making such inferences introduces error because the sample may not represent the population. The laws of sampling error tell us that the average of all possible samples drawn from a population will reflect the population; however, any single sample may not. For instance, we do not expect four cards (a sample) dealt from a deck (the population) to always contain exactly one card of each suit.
FMEA - Failure Mode Effects Analysis. Determination or prediction of how an entity (product, service, process, machine, etc.) will fail and the effects (including severity) of the failure. Sometimes the severity, impact, or importance of the results of a failure is emphasized in FMEA by inserting a "C" for criticality (FMECA). Sometimes the entity under consideration is highlighted by replacing the "F" with a symbol for the entity, e.g., Production Mode Effects Analysis (PMEA).
Inspection - determination of a product's or service's level, amount, or condition of a quality characteristic. Testing determines the properties of a thing. Inspection determines if the thing's properties have the intended value.
Interval - a scale with equidistant values and values below zero, for example: Fahrenheit.
ISO 9000 - a series of five standards known as ISO9000-9004 or (in the USA) Q90-94.
JIT - just in time - a philosophy of providing services and products that strives to eliminate all waste, especially the wastes of work in progress, set-up time, inventory, and waiting. JIT strives to deliver just what is needed (parts, information, etc.) to just where it is needed just when it is needed. Ideally, whoever produced an item (part, information, etc.) would produce it just as needed by the next process and it would be delivered to the next process without delay, oriented (conditioned, prepared, etc.) just as needed by the next process. Before JIT can be implemented, the processes of an organization and its suppliers have to be in control. JIT works best with a pull system. CANBAN is an often used JIT and pull system technique.
Leadership - inspiring others toward common goals. A quality system needs leaders. The lead leader should be the chief executive officer (CEO). If an activity is to be accomplished, a goal is to be reached, a team is to be successful, etc. there must be leadership.
Loss function - Taguchi loss function - any deviation from the ideal creates a loss in quality, and the greater the deviation the greater the loss. Compare this philosophy to: if it is within toleranceit is OK. Consumers inherently consider quality according to the loss function - the closer a product or service is to the consumer's ideal, the more satisfied the consumer is. The loss function is stated numerically as: L = K (Y - T)2, where L = loss in dollars, K = a cost coefficient, Y = the actual quality value, and T = the target or ideal quality value.
Lot - batch - a quantity of product or materials. An aggregate of units. The units do not have to be single items.
Mean - the arithmetical average. The mean of a population is represented by µ; the mean of a
sample by , pronounced X-bar. A bar over any variable symbolizes an average value for that
variable. A double or triple bar symbolizes the grand mean or average of several averages.
Useful when using an interval or ratio scale.
Median - the midpoint in a list of ordered values. Useful when using an ordinal scale.
Mode - the most frequently occurring value in a distribution. There may be more than one mode or no clear mode. Useful when using a nominal (categorical) scale. Modular systems - broad standardization techniques. Macros are used in software applications to simplify, standardize, and speed processes. Similarly, forms, templates, work methods, parts, assemblies, inventory and transport mechanisms, procedures, systems, ad infinitum are used to decrease variability within and simplify the preceding. The modular approach reduces to a minimum the various components of a system and maximizes the compatibility or complimentary features of the components. For example: in a modular storage system all items, parts, etc. would be stored in functionally identical containers of different sizes. The sizes would be kept to a minimum and would all be multiples of a standard module size. The containers would all be storable (stackable, insertable into a storage compartment, etc.) by the same method. The containers would also all have the same labeling/identification scheme. Another example is drafting paper. D size paper is twice as large as a C size, which is twice as large as B size, which is twice as large as A size paper.
Noise factors - environmental factors - there are influences (factors, parameters, variables) that affect processes in a non-controllable or hard-to-control manner, for example: the humidity when air drying lumber or the strength of a laborer. Through design of experiment (DOE) techniques, the level or value of a controllable factor or factors can be changed so that the influences of noise factors are diminished, thereby maintaining quality despite the level of the noise factors. A process thus designed is called a robust design. In ANOVA, the noise is the error variation or SSE.
Nominal or categorical - a pseudo-scale that can only label groups and count the frequency of items in each group, for example: 20 scratches, 8 dings, or 14 defects.
Nonconformity - A departure of a quality characteristic from its intended level that causes the product or service not to meet a specification (quality in intent). A nonconformity might be so because of defects, however, a defect does not automatically imply a nonconformity. Many defects are of a minor nature and do not imply a reject.
Operating characteristic curve - a plotted curve showing the relationship between the consumer's risk and the process average. From an operating characteristic curve it can be determined what the probability is of failing to detect a nonconforming lot given various process averages.
Ordinal - a scale where rank order is indicated but the distances between scale points are not known, for example: the 1st place, 2nd place, and 3rd place winners; the favorite food, the next favorite food, etc.; or the 1st shipment, the 2nd shipment, etc.
Parameter - an index or label that describes some characteristic of a population. In statistics the mean, standard deviation, etc. are parameters. In production, the RPM, feed rate, cycle time, cost per unit, etc. are parameters. Parameters have values, for example: a mean of 4.2, an RPM of 400.
Poisson distribution - a discreet distribution, where the mean and the variance have the same
value (). The number of defects occurring in a part (or lot) often is well modeled by the Poisson
distribution. In SPC, the average number of defects is represented by 
when the unit or lot size
is constant. When lot size varies, 
represents the average number defects per unit.
Population - the universal set of all things, units, parts, items, subjects, or observations, etc. having some common characteristic. A population is often considered infinite. For example, an infinite number of rolls of a die. Whether a set of data is considered a population or a sampledepends on what needs to be known about the data and/or if knowledge of the data set in question is to be used to make inferences about other data sets. In shop talk, population and sample terminology are often used interchangeably.
Precision - the ability to repeat the measurement and get the same result. Also, called consistency, reliability, and repeatability. Precision may exist to a high degree without accuracy. For example: Jack measures a part 10 times and gets 2.25 every time, however, the part is actually 2.50. Conversely, great accuracy can exist with little precision. For example: You weigh yourself on a bathroom scale 10 times in succession. The average of the measurement is 180 lbs. However, individual measurements vary from 170 to 190 lbs. You weigh in reality exactly 180 lbs. The scale is highly accurate but not very precise.
Process control - uses statistics and other means (such as ABC, DOE, PVA, etc.) to reduce the cost, variation, and cycle time of processes to a minimum while still producing the intended quality. Process control involves knowing the steps in a process, causal relationships among process parameters, and associated costs, times, etc.
Process capability - every process will vary in its output due to random error. This is true even
when all sources of assignable error are removed. The natural variation that a process produces
(usually a normal distribution) is its capability. To be able to produce all parts within
tolerances, the process capability limits must be within the tolerance limits. Often, a given
process will be incapable of producing within tolerance limits. When this is the case, labor is not
to blame; it is impossible to produce all good parts. The capability ratio is 
.
The capability index is 
. CR has to be < 1.0 (.75 is standard), or conversely
CPhas to be > 1.0 (1.33 is standard), to be able to produce all parts in tolerance.
Producer's risk - type I error - - the probability of making the false decision that a lot of product is nonconforming when actually it is conforming, likewise, the probability of finding that a process is out of control when it really is in control.
Pull system - a system of production where parts are delivered to a process by request of that process. Ideally, parts are not requested until needed and the parts are not manufactured until needed. In actuality, lots or batches of parts are requested when needed. The final assembly process initiates the requests. A cascade effect is thus initiated where each preceding process requests the needed parts from previous processes. What makes this different from a push system is that in a pull system no preceding process ever makes an extra part to be placed in inventory and/or used as a buffer. Preceding processes only make parts when they are requested to do so by the latter process which needs the parts. Furthermore, the latter process has a minimum buffer (ideally one batch or lot) and lots are keep to a minimum (ideally one). For example: station #3 on an automobile final assembly line installs the engine. The lot size is two (two engines on a pallet) and the buffer in one lot. Station #3 will not request another lot until its buffer is depleted, e.g., until it only has two engines left to install. Engine assembly will not have a stockpile of engines. Engine assembly might have a small buffer of parts to make engines. Obviously, in a pull system parts have to be made and delivered very fast. In a traditional system, production is planned well in advance of when products need to be delivered. Accordingly, subassemblies needed for final assembly are ascertained and the production or lead time for each subassembly, its subassemblies, etc. are calculated. Margins of error, scrap rates, down-time percentages, etc. are factored in. In order for customers (including internal customers, i.e., a latter process receiving from an earlier one) to receive items in a shorter period, inventories of materials and parts are kept. Traditionally, work in progress, stockpiled parts, inventory, storage, and lead times are considered normal - they are all wastes that a pull system eliminates or minimizes.
PVA - Process value analysis - a method to determine how much value and cost each process adds to a material, product, or service, and how to reduce costs and increase value. The basic steps are to describe and analyze the activities in the process, analyze the cost drivers, identify the improvements, and make the improvements. In PVA, analyzing a process is done to identify value-adding activities, necessary non-value-adding activities, and waste. Cost drivers are the characteristics of activities that add to the activity's cost. The goal is to eliminate waste, decrease to a minimum non-value-adding activities, and through improvement of processes decrease the cost of non- and value-adding activities. PVA requires activity-based accounting (ABC).
Q90 - definitions and guidelines for selection and use of the following standards.
Q91 - quality assurance model for design/development, production, installation, and servicing. The most encompassing and stringent standard. Ex: Q91, 4.15.2 - The supplier shall provide methods and means of handling that prevent damage or deterioration.
Q 92 - quality assurance model for production and installation.
Q 93 - quality assurance model for final inspection and test.
Q 94 - guidelines for quality systems elements and management.
QFD - quality function deployment - a system of design and manufacture that focuses on
consumer-defined quality and ensures secondary quality characteristic (such as tolerances and
quality control) stay aligned with consumer-defined quality. Tolerances, inspection schemes,
SPC, and others are not ends - they are means. The end goal is a satisfied customer. To say that
a car must ride smooth is a primary quality characteristic. To say that the allowance between the
ball and the joint is .001, is a secondary quality characteristic that is irrelevant to the customer.
QFD works will with CE but follows traditional design stages. In QFD, the requirements of each
stage drive the requirements of the next, keeping in mind that customer requirements drive the
process. Each stage and the entire process is evaluated against the standard of satisfying
customer requirements. The steps are: customer requirements design requirements engineering
design product characteristics manufacturing and purchasing operations/processes production
(including quality) controls documentation and packaging delivery to customer service to
customer quality as perceived by customer.
Quality
Quality characteristic - a feature of a product, part, material, service, etc. used in determining quality.
quality of design - the degree to which a design (assuming, the design can be implemented perfectly) will satisfy fitness for use requirements.
quality of intent - the degree to which a product or service is produced or delivered according to its design.
quality of perception - the degree to which the customer perceives the product or service satisfying their needs.
Quality of process - process quality - the degree to which errors are reduced and cycle times are shortened.
Range - difference between lowest and highest values. A measure of the spread of scores.
Ratio - a measurement scale with equidistant values and an absolute zero, for example: Kelvin, length, time, or weight.
Robust - a situation little affected by noise or environmental factors (a low signal to noise ratio). In a very robust design, many parameter values can fluctuate, however, the results will have the intended quality.
Sample - a subset of the population. A group of things, units of observation, trials, measurements, values, etc.
Sampling plan - a specific set of criteria (usually as a table) to be used to determine acceptance or rejection of a sample. There are different tables for single, double, and multiple sampling; normal, loosened, loosened and tightened inspection; and utilizing the range or standard deviation and other options when inspecting variables. Plans contain data concerning the accept and reject criteria for various combinations of sample sizes and AQL's.
Sampling scheme - a combination of sampling plans with switching rules for decreased and tightened inspection. Various sampling schemes exist for: single and multiple sampling, utilizing the range or standard deviation when using variables sampling, and for different levels of consumer and producer's risks.
Sampling system - a collection of sampling schemes. Sampling schemes include: standardized procedures for utilizing different schemes, associated operating characteristic curves, and various inspection levels that determine the relationship between lot size and sample size. Two often used sampling systems are: 1) ANSI/ASQC Z1.4-1993: Sampling Procedures and Tables for Inspection of Attributes; and 2) ANSI/ASQC Z1.9: Sampling Procedures and Tables for Inspection by Variables for Percent Nonconforming.
Scrap - leftover material (and associated labor and overhead). If you cut a 2-foot diameter circle out of the center of a full sheet of plywood you are producing more scrap than if you cut it out of a corner. Less scrap = less expenses = lower prices and/or more profit. In common shop terminology, defective materials, parts, and products are called scrap; they are more correctly called defectives or rejects. Scrap may be recyclable or useful for another function or it may be waste. Waste and scrap are often used incorrectly as synonymous terms.
Sensitivity - the ability to discriminate between measurement points. A ruler graduated in 1/4 inch increments is not as sensitive as one graduated in 1/50s of an inch. A pharmacist's scale is more sensitive than a truck scale.
SMED - single minute exchange of die. Pertains to the shorting of down-time between setups. Analyzes which tasks have to be performed with operations ceased (internal tasks) and those that can be performed with operations continuing (external tasks). Key points are to: 1) categorize tasks (broken down as discreetly as possible) as internal or external, 2) move as many internal tasks to external as possible, and 3) minimize task times. Oversimplified example: after a batch of parts is machined, the operator gets a new work order and changes tooling. The new work order could be on hand before the previous order was completed. The only thing the machine has to be stopped for is changing tooling.
SPC - statistical process control. Through use of various types of control charts and other data gathering instruments and analysis of events and data, processes to produce product or deliver services are controlled. The statistical tools employed are primarily based on a test of the difference between what can be expected (normal variance) and what actually is. That is, if deviations from the ideal are indications of random error or an out of control process, and conversely, if a process in specs is actually being affected by attributable errors.
Standard deviation - a mathematically derived measure of the spread of values in a normal distribution. The square root of the variance of a set of values.
Statistic - an index or label describing a characteristic of a sample; an estimate of a
populationparameter based on a sample; the value of a sample characteristic. The mean of a
population, µ, is a parameter; 
is the mean of a sample and therefore a statistic.
Statistical acceptance sampling - an inspection system that utilizes the known behavior of random error to estimate the percent nonconforming in a lot by investigating only a sample of that lot.
Statistical tolerancing - when total tolerance of a stack of parts needs to be a certain amount, for example .010, the tolerances of each part in the stack are traditionally calculated so that if every part were at its maximum or minimum material condition the stack would still be in tolerance. Every part is unlikely to be at either the maximum or minimum condition. Statistical techniques can be employed which maintain or improve the percent of nonconforming product (the part stack) while loosening the tolerances on each part. Furthermore, the relative difficulty or expense in producing a given part to tolerance can be considered. Non-critical and/or very hard to produce tolerances can be maximized, while easy and/or inexpensive to achieve tolerances are keep tight.
Strategic planning - is different from long-range planning. Strategic planning considers an organization's goals and resources to most advantageously position the organization to win - today, tomorrow, or 20 years from now.
Taguchi methods - Taguchi, like Deming, Ishikawa, Juran, etc. had many ideas. Among his many
contributions are his: concept of loss function, ANOVA experimental designs applied to quality,
and categorization of quality efforts into: 1) design - designing quality into services, products,
and the systems used to deliver and produce them, 2) production/delivering - maintaining quality
of intent, and 3) refinement - refine the ongoing process via design of experiments (DOE).
Team
Tolerance - the maximum variation allowed. Tolerance is a single quantity that may be stated in a ±, unidirectional, or bidirectional fashion.
Type I error - see producer's risk.
Type II error - see consumer's risk.
Unit - unit of inspection - The thing(s) that comprise(s) the lot and sample. The unit need not be a single item. An entire newspaper, a hair cut, 100 feet of rope, meal service, 10 yards of carpet, a baseball game, a barrel of oil, 50 lbs. of nails, a dozen eggs, a pair of socks, ad infinitum could each be the unit inspected.
Universe - a group of populations. A universe is a set of populations where all populations are comprised of items with similar characteristics but each population may be described by different characteristics, for example: within the universe of trucks we might be interested in the MPG of the population of trucks made by Ford, the carrying capacity of the population of GM trucks, and the safety record of Dodge trucks. We probably would not measure all trucks in each population. We would investigate a sample of each population.
Value - the level, quantity, label, amount, etc. of a factor, feature, component, statistic, or parameter.
Variable - a value of a characteristic, parameter, or statistic that can vary as to its quantity, amount, category, etc., especially interval or ratio data quantified on a continuous scale.
Variance - the spread or dispersion of values in a distribution. Mathematically, the square of the standard deviation.
Variation - deviation from the intended condition. Variation in production and service delivery is almost universally bad. Most quality and management techniques are aimed at reducing variation.
Waste - refers to non-usable and/or non-value adding entities. Waste can be in the form of material, motions, missed opportunities, and numerous other things. Every motion not adding value to a product or service is waste. Some waste may be necessary but decreasable, e.g., transport of material; some may be necessary and not decreasable, e.g., shipping; much can be eliminated. If a lumber mill does nothing with the sawdust produced, the sawdust is waste, as is the time, money, and labor to discard it.
Work place basics - the attributes that all employees must possess to be competent at any job.
The following are often stated work place basics: academic basics - the general communications,
quantitative reasoning, and technological literacy skills required of all employees; adaptability - to
change and new situations; creative thinking/problem-solving skills; flexibility - multi-tasking
ability, cross-trained; and teamwork skills.
