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A computer system determines a quantitative measure of a manufacturer's capability to achieve a product requirement at an acceptable cost. This quantitative measure, called the manufacturer's capability curve, is a function relating a product requirement, such as a customer's need or a government regulation or other performance requirement of a component of the product, to a cost for achieving this product requirement. The use of the computer system is enhanced by following a methodology for identifying possible key characteristics as described below. This methodology allows for identification of the relationship of lower level features to higher level features of a product and identification of interaction between two or more features and their impact on product performance.
1. A computer system for analysis of manufacturing costs, comprising:
means for receiving and storing an indication of an engineering specification of a product feature indicating a performance measure of the product corresponding to a plurality of feature values for the product feature;
means for receiving and storing an indication of a manufacturing capability distribution for the product feature indicating a probability that a desired feature value is obtained with a manufacturing process;
means for receiving and storing an indication of a unit cost of the product feature; and
an analysis module having inputs for receiving the engineering specification, the manufacturing capability distribution and the unit cost of the product feature and an output providing an indication of an adjusted unit cost of the product feature as a function of the performance measure of the product corresponding to the product feature.
2. The computer system of claim 1, wherein the analysis module comprises:
a cost analyzer having an input for receiving the unit cost and the manufacturing capability distribution and an output providing an adjusted unit cost; and
a capability analyzer having an input for receiving the engineering specification and a second input connected to the output of the cost analyzer to receive the adjusted unit cost, and an output providing the indication of the adjusted unit cost as a function of product performance.
3. The computer system of claim 2, wherein the cost analyzer comprises:
means for selecting a desired nominal value;
means for determining the manufacturing capability distribution as a function of one variable;
means for computing the adjusted unit cost by dividing the unit cost by the manufacturing capability distribution.
4. The computer system of claim 3, wherein the capability analyzer comprises:
means for selecting feature values of the product feature;
means for determining a performance measure corresponding to the selected feature value from the engineering specification;
means for determining an adjusted unit cost corresponding to the selected feature value; and
means for determining manufacturing capability as a function of the performance measure according to the determined adjusted unit cost and the determined performance measure.
5. The computer system of claim 2, wherein the capability analyzer comprises:
means for selecting feature values of the product feature;
means for determining a performance measure corresponding to the selected feature value from the engineering specification;
means for determining an adjusted unit cost corresponding to the selected feature value; and
means for determining manufacturing capability as a function of the performance measure according to the determined adjusted unit cost and the determined performance measure.
6. The computer system of claim 1, further comprising:
means for receiving an indication of required performance of the product and acceptable cost of the product feature; and
means for displaying an indication of the required performance and the acceptable cost in correspondence with the indication of the adjusted unit cost as a function of product performance.
The United States of America has certain rights in this invention as provided for by the terms of Contract No. F33615-94-C-4428 and Contract No. F33615-94-C-4429 awarded by the Air Force Office of Scientific Research.
Present invention is related to computer systems and computerized processes for analyzing manufacturing processes and engineering specifications to obtain accurate cost estimates of a manufactured product.
A significant problem in manufacturing is determining the relationship between customer needs or other product requirements and the cost of manufacturing a product to meet those needs or requirements. One methodology currently used in some major corporations involves the identification of key characteristics. Key characteristics in general are product features, manufacturing process and assembly process parameters that significantly affect product performance, function and form, particularly as they relate to customer satisfaction and product safety. The key characteristic identification methodology provides a focus on important product, manufacturing and assembly features to help reduce development time, reduce costs, and improve the quality of products.
One methodology for identification of key characteristics uses a Taguchi loss function (TGL). See Phadke, Madhav S., Quality Engineering Using Robust Design, AT&T Laboratories, Prentice Hall, N.J., 1989. A TGL represents qualitatively and anecdotally perceived cost losses incurred as a function of customer dissatisfaction from diminished product performance and function due to a variation of a product feature from its nominal engineering specification. However, since TGLs are generally qualitative and anecdotal, and are generally not obtained in any quantitative manner, decisions based on such TGLs may be based on incorrect assumptions.
Referring now to FIG. 1(a), a manufacturing capability distribution is shown at 20 while a TGL is shown at 22. In FIG. 1 (a), the product feature is not a key characteristic because variations in the product feature due to the manufacturing capability distribution do not significantly contribute to qualitative cost. However, FIG. 1 (b) shows a feature which is a key characteristic since the manufacturing capability distribution, shown at 24, results in variations in the product which significantly affect a perceived cost, shown at 26. The variation in the manufacturing process or the design needs to improve for this product feature. In FIG. 1 (c), the manufacturing process is precise as indicated by curve 28, but does not reach its target 32. This deviation from the target causes the feature to be a key characteristic since the perceived cost as a indicated by curve 30 is increased, and requires improvement in the ability to meet the target characteristic of the feature.
A significant problem in the implementation of a key characteristic identification methodology is due to the generally qualitative and anecdotal nature of Taguchi loss functions. That is, TGLs are generally defined in terms of an assumed shape, which may be based on a small set of customer reports on product performance or in some cases based on assumptions or speculations about what such information might be. Therefore, the TGL may be inaccurate and thus lead to incorrect decisions. For example, a lot of time, money and effort may be spent solving a problem which is not significant, or an important problem may be overlooked. Additionally, features selected for analysis to determine their key characteristic status are often selected reactively, in response to customer dissatisfaction, or based on assumptions by engineers. The lack of a systematic way to identify KCs may result in an important problem being overlooked.
The problems due to the qualitative nature of TGLs can be overcome by using a quantitative measure of a manufacturer's capability to achieve a product requirement at an acceptable cost. This quantitative measure, called the manufacturer's capability curve, is a function relating a product requirement, such as a customer's need or a government regulation or other performance requirement of a component of the product, to a cost for achieving this product requirement.
Accordingly, one aspect of the present invention is a computer system for analysis of manufacturing costs. This computer system receives an engineering specification for a product feature, correlating product performance to the product feature. A manufacturing capability distribution for the product feature is also received, which indicates a probability that the manufacturer can make the product feature have a target value, such as size. Cost information, indicating a per unit cost, is also received. The computer system includes an analysis module having inputs for receiving the engineering specifications, manufacturing capability distribution and cost information and an output providing a quantitative relationship between the performance measure and cost of manufacturing the product with the product feature.
The use of the present invention is also enhanced by following a methodology for identifying possible key characteristics as described below. This methodology allows for identification of the relationship of lower level features to higher level features of a product and identification of interaction between two or more features and their impact on product performance. This approach is fundamentally different from the practice in some industries where only problematic features are flagged as KC's.
In the drawing,
FIGS. 1A through 1C illustrate existing methods for identifying key characteristics according to manufacturing capabilities and Taguchi loss functions;
FIG. 2 is a hierarchical tree indicating relationships of key characteristics;
FIG. 3 is a diagram of a product architecture for an aircraft horizontal stabilizer;
FIG. 4 is a cross-sectional perspective of a diagram of a half shaft;
FIG. 5 is a block diagram of a computer system;
FIG. 6 is a schematic diagram of a memory system;
FIG. 7 is a perspective view of a computer work station;
FIG. 8 is a data flow diagram of one embodiment of the present invention;
FIG. 9 is a data flow diagram illustrating more detail of the analysis module 108 of FIG. 8;
FIG. 10 is a graph illustrating the relationship of performance of a product to a value for the feature;
FIG. 11 is a graph illustrating a manufacturing capability distribution for achieving a product feature;
FIG. 12 is a graph of a typical adjusted unit cost function where the desired nominal value of the product feature is a maximum;
FIG. 13 is a graph of a typical adjusted unit cost function where the desired nominal value of the product feature is a minimum;
FIG. 14 is a graph of a typical adjusted unit cost function where the desired nominal value of the product feature is a mean;
FIG. 15 is a graph illustrating the relationship between average cost versus performance, for several standard deviations for a manufacturing capability distribution, and a customer's acceptance space;
FIG. 16 is a flow chart describing a process performed by the cost analysis module 112 of FIG. 8; and
FIG. 17 is a flow chart describing a process performed by the capability analyzer 116 of FIG. 8.
The present invention will be more completely understood through the following detailed description which should be read in conjunction with the attached drawing in which similar reference numbers indicate similar structures.
A computer system is used to determine a quantitative measure of a manufacturer's capability to achieve a product requirement at an acceptable cost. This quantitative measure, called the manufacturer's capability curve, is a function relating a product requirement, such as a customer's need or a government regulation or other performance requirement of a component of the product, to a cost for achieving this product requirement. The use of the computer system is enhanced by following a methodology for identifying possible key characteristics as described below. This methodology allows for identification of the relationship of lower level features to higher level features of a product and identification of interaction between two or more features and their impact on product performance.
There are three fundamental categories of key characteristics: product (PKC), manufacturing (MKC), and assembly (AKC). PKCs are the geometric features, material properties, information or energy of a product that are highly constrained or for which minute deviations from nominal specifications, regardless of manufacturing capability, have a significant impact on the performance, function and form of the product at each product assembly level. PKCs are permanent for a given product architecture. PKCs are thus associated with the important physical properties of the product that are needed to meet a product requirement. Although there may be many features that are needed to meet a product requirement, the PKCs are those features which, when a change is made, significantly affect the product requirement. Assembly and manufacturing capability are not initially considered in defining a PKC. However, iterations might need to be conducted to ensure that a selected set of PKC's can be manufactured or assembled properly.
MKCs include manufacturing machine process parameters and/or fixturing features for machine tools and equipment that significantly affect the realization of a PKC or an AKC at the detailed feature level. MKCs are permanent for a given manufacturing process. For example, the run out of a shaft diameter may be considered a PKC if it affects an important customer requirement of rotational balance and vibration when the shaft is spinning at high speeds. Experimental design might show that the rotating speed and cut depth of a machine for making the shaft have a significant impact on shaft run out. Both of these characteristics of the machine would be MKCs and would be permanent for the product unless the manufacturing equipment, process or design changes. With MKCs defined, the machine operator can focus on monitoring and controlling the rotating speed and cut depth with the understanding that these process parameters ultimately affect product vibration requirements that satisfy customer needs.
AKCs include the product, tools, fixtures and procedures, during each assembly stage, that significantly affect the realization of a KC at the next higher assembly process level during the assembly process. AKCs are permanent for a given assembly process. For example, a given design may have several options for assembly processes, including match-drilling, pin in slot, pin in hole, etc. Each candidate assembly process has a different set of a AKCs to generate the required PKCs. For example, in an aircraft, holes on temporary portions of the skin panel might be needed for positioning the skin during rivet hole drilling operations. The location of rivets on the skin panel are considered PKCs because of fatigue strength and aesthetic issues. The temporary locating holes used to create the PKC are thus AKCs. Tooling and fixture locating features such as surface, hole and edge locators that affect PKCs also might be AKCs.
AKC that cannot be achieved with current manufacturing capability is referred to herein as a StatKC. StatKCs are a subset of KCs that add significant risk to successful delivery of the product because the PKCs cannot be properly manufactured or assembled at the required cost, quality and/or schedule time. StatKCs are eliminated when the PKC problem is permanently solved.
The KCs may be considered as forming a hierarchical tree structure where the high level KCs flow down into the lower level KCs and the low level KCs combine to create the high level KCs. However, the tree generally is not strictly hierarchical since a KC may contribute in conflicting ways to two or more high level KCs. AKC flowdown provides a view of the product requirements and how the low level features combine to meet the customer requirements. FIG. 2 illustrates a KC tree which shows how KCs are flowed through the product development process. The left-hand side of the figure shows the PKCs at 40. The decomposition of the product architecture leads to the MKCs 42 that create the detailed part features. The right-hand side of the figure shows the AKCs at 40. Upon completion of the manufacturing processes, the parts are assembled using processes, tooling and fixtures to create the production composition. The product development process should be based on an understanding of the KCs on both sides of the tree. FIG. 2 also shows the associated KCs and the double-ended arrow 46 depicts that the three categories of KCs should be assessed concurrently during product development because product and process designs are highly linked.
A product architecture provides another way of breaking the product into manageable parts. Such a decomposition assists management of design of a complex product, so that portions of the product are designed by separate design teams. FIG. 3 shows an example product architecture for an aircraft. Given a product architecture, each portion of the product has a set of associated KCs. However, there generally is not a one-to-one mapping between the KC tree as shown in FIG. 2 and the product architecture tree, such as shown in FIG. 3.
PKCs are identified using a flowdown process from high level product requirements down to low level product features. This flowdown process is a process of decomposition and "trimming," which in general involves the following steps.
First, high level PKCs are identified, preferably quantitatively. Without quantitative requirements, it is difficult to measure product performance, function or form and thus difficult to assess if a product design has met its goals. Product requirements can come from several sources including US government regulations (such as FAA and FMVSS), regulations of countries where products will be sold, end-user customer requirements, and corporate product, safety and environmental requirements. Qualitative customer requirements can be translated into quantitative engineering specifications using Quality Function Deployment (QFD). See "The House of Quality," by J. R. Hausing et al., in Harvard Business Review, May-June 1988, No. 3, pp. 63-73.
Second, features at a level n+1 of a product architecture decomposition are determined, such that these features are those which combine to create the PKCs at level n. Assume n has a value of 1 at the customer requirements level and increases with the current level of decomposition. There may be more than one feature to choose as a PKC. In such a case, that feature to be chosen is one which is most likely to be shared by other PKCs or one that appears reasonable. The second step is then repeated until the detailed level of dimensions on parts is achieved (e.g., diameter of a pin, width of a sheet, etc.) or until the decision on what feature should be chosen is dependent on the manufacturing process. The PKC tree does not have to be and generally is not a pure hierarchical decomposition. PKCs at level n may contribute to more than one PKC at level n-1 or on other levels n-x. Second, different branches of the PKC tree may have different depth. The number of the PKCs should be minimized while not sacrificing the usefulness of the flowdown.
Similar AKC trees can be developed following this process; however, there may not be a one-to-one correlation to the PKC tree because assembly composition and processes would most likely be different from the product architecture. Additionally, MKCs may be identified through a design of experiments in view of the PKCs. Iterations of the identification process of the PKCs, AKCs and MKCs may be done.
The relationships between the KCs of a product should be well defined. An agile organization should be capable of defining the relationships between the KCs and the function of the product. This is useful for making tradeoffs between two KCs, understanding the effects of changes on the macroscopic view of the product, doing sensitivity analysis of the product (i.e., the effect of manufacturing variation), and providing to the rest of the design team a description of the interactions.
In order to make accurate tradeoffs, determine the effects of changes quickly and to understand the contributions of other subassemblies on a given KC, the KC is related to lower level KCs through relationships such as, but not limited to, an equation, such as KC=f (KC1, KC2 . . . ) or a relationship defined by results of a design of experiments and regression analysis.
Given the identified KCs, a StatKC identification process can be conducted. In this process, some or all of the KCs of a product are analyzed by combining engineering specifications, manufacturing capability and cost information. This analysis will now be described in connection with FIGS. 4-16. As an example product feature, FIG. 4 shows a front-wheel drive half-shaft, which is a component in a front-wheel drive power train. A half-shaft transmits power from the automobile transmission to a front-wheel with continuous velocity. There are two continuous velocity joints in a half-shaft. The first joint 50 is connected to the transmission (not shown) and connects a shaft 54 to the second joint 52. The second joint is then connected to the wheel (not shown). It has been found that a feature of one of the continuous velocity joints has a high correlation to a performance measure of the half-shaft. Such a correlation, in combination with knowledge of the manufacturing capability to achieve the desired feature and cost information, may be used to determine whether a performance requirement can be met at an acceptable cost in a customer's acceptance space. A general purpose computer system which receives these three pieces of information or assists in their generation is an aspect of this invention which can be used to assist in key characteristic analysis. Such a computer system will now be described.
A computer system with which the present invention may be implemented will now be described in connection with FIGS. 5-7. FIG. 5 shows a computer system 60 including a processor 62 connected to a memory system 64 via an interconnection mechanism 66. Input devices 68 and output devices 70 are also connected to the processor and memory system to communicate their width through the interconnection mechanism 66. The computer system 60 may be any of a number of commercially available general purpose computing systems. Such personal computer systems typically employ commonly available processors, such as the x86 series microprocessors from Intel and the 680x0 series microprocessors from Motorola. Other suitably programmed microprocessors may be used. The interconnection mechanism 66 may be a simple bus, or may involve a more complex switching arrangement to allow the various elements of the computer system to communicate in parallel. It should also be understood that the invention is not limited to a single processor system.
An operating system (not shown) controls the execution of application programs and provides scheduling, debugging, input/output, memory management, data management, and related services on the computer system 60. The combination of the operating system and computer hardware define a computer platform or computer system. Such a computer system may be programmed using high level programming languages, such as "C" or other programming language to create an application program, which has a machine executable code created by compiling a computer file containing a program in the high level programming language. Such a high level programming language, or an application program such as a commonly available spread sheet program may be used to implement the system described below in connection with FIGS. 8-17. In one embodiment, a Macintosh Duo, from Apple Computer, of Cupertino, Calif., using the System 7.5 operating system and the Excel spreadsheet program available from Microsoft are used. The spreadsheet program is used to receive input data and process the input data according to the process described below.
Exemplary input devices which may be used with the computer system 60 include a mouse, a track ball, a pen and tablet, or other pointing devices, as well as keyboards, key pads, scanners, and other commonly used input devices for general purpose computers. The output device 70 may be a cathode ray tube (CRT) display, liquid crystal display (LCD), of which there are a number of types and other display devices such as a printer.
FIG. 6 shows more details about the memory system 64 of FIG. 5. The memory system includes a computer readable and writable, random access, non-volatile recording medium 80, such as a magnetic disk or optical read/write disk. The disk may be removable, known as a floppy disk, or permanent, known as hard drive. Such a disk has a number of tracks as indicated at 82 in which signals are stored, typically in binary form, i.e., a form interpreted as a sequence of ones and zeros such as shown at 84. Such signals may define a computer program to be executed by the microprocessor, or information stored on the disk to be processed by a computer program. Typically, in operation, the processor 62 causes data to be read from the disk 80, using for example a magnetic head 84, into an integrated circuit memory element 86. The integrated circuit memory 86 allows for faster access by processor to the information than does the disk 80. The processor generally manipulates the data within the integrated circuit memory and then copies the data to the disk 80 when processing is completed. A variety of mechanisms are known for managing data movement between the disk 80 and the integrated circuit memory 86, and the invention is not limited thereto. It should also be understood that the invention is not limited to the particular input devices or output devices, the operating system, high level programming languages, processor or memory system used.
The computer system may be in the form of a work station such as shown in FIG. 10 which includes the general purpose computer embodied in a container 90 connected to the output display 70 and input such as a key board 68. The display may illustrate graphs or other information to the user.
One embodiment of a system in accordance with the invention will now be described in connection with FIG. 8. Given an identification of a key characteristic according to any ethodology including the methodology defined above, its status as a "StatKC" may be analyzed. To perform such an analysis, data correlating product performance and feature value, herein called the engineering specification 100 shown in FIG. 8, is used. The engineering specification 100 may be obtained analytically, by using computer analysis (e.g. Finite element analysis), or engineering analytical methods, or empirically. Experiments may be conducted using a design of experiments (DOE) such as described by Taguchi. See Phadke, Madhav S., Quality Engineering Using Robust Design, AT&T Laboratories, Prentice Hall, N.J., 1989. Experiments may be conducted to determine a correlation between the desired performance defined as a key characteristic and the range of various embodiments of particular feature (a lower level KC) affecting the key characteristic. For example, the correlation between performance K (a high level KC) and feature value X (a lower level KC) may be described by an equation such as equation (1) derived from regression analysis from the results of a DOE:
This correlation may be represented by a curve 102 as in the graph of FIG. 10. In FIG. 10, the feature value X is shown on the abscissa and the performance K is shown on the ordinate. Typically, the feature value is a dimension, i.e., size, but also may be its composition or other measure of state rather than performance. For the sake of simplicity, the description that follows is given using feature size as the feature value.
Referring again to FIG. 8, an analysis of a StatKC also uses a manufacturing capability distribution 104. An example distribution is shown by curve 118 in FIG. 11. The manufacturing capability distribution is defined by the probability that a particular component having a given target size actually has the target size when manufactured. Additionally, some of the manufactured parts are acceptable while others are unacceptable given certain minimum and maximum values. Most manufacturing organizations maintain such information (e.g., statistical process control data) as a measure of their capability to achieve certain specifications. This distribution generally fits a normal Gaussian distribution, or other standard form of probability distribution. A mathematical definition of this distribution can therefore be determined. For example, given a normalized standard deviation Z, a minimum and maximum feature sizes centered around a mean, e.g., MIN and MAX, a manufacturing process mean μ (the average of MIN and MAX, shown in FIG. 11 on the abscissa) and a manufacturing standard deviation σ, the probability of acceptable parts is given by the following equation (2), assuming a normal distribution:
P=P Z<(MAX-μ)/σ!-P Z<(MIN-μ)/σ!. (2)
Unit cost information for making a product feature such as a product component, including labor material and overhead but generally not including scrap and rework, is also typically known by a manufacturer. This unit cost information is indicated at 106 in FIG. 8. In the example of the half-shaft feature discussed above, the unit cost of the product component is fifty-five cents.
Referring to FIG. 8, an analysis module 108 receives an engineering specification 100, a manufacturing capability distribution 104 and cost information 106 and processes that information to provide a manufacturer's capability curve, indicated at 110, which is a representation of an adjusted unit cost for making the product feature with respect to a performance related to the product feature.
A manufacturer's capability curve is described in more detail below. The process performed by analysis module 108 to obtain a manufacturer's capability curve will now be described in connection with FIGS. 9 and 16. Referring now to FIG. 9, the manufacturing capability distribution 104 and cost information 106 are input to a cost analyzer 112 to obtain an adjusted unit cost 114. The adjusted unit cost is obtained by distributing the cost of all parts outside the MIN/MAX range (i.e., the rejected parts) over the cost of the good parts. This distribution is made by dividing the unit cost by the manufacturing capability distribution. Hence, the adjusted unit cost given the example data above is fifty-five cents divided by P, where P is the probability function defined above.
The function of the cost analyzer 112 and typical adjusted unit cost functions will now be described in more detail in connection with FIGS. 12-14 and 16. The cost analyzer 112 receives the manufacturing capability distribution which is a function of a mean μ, minimum MIN and maximum MAX of the feature size. Other values in the distribution are assumed to be fixed. Additionally, a desired nominal value of the feature size is selected as either the MAX, MIN or μ. The desired nominal value means the feature size which provides the best performance. Other values away from the desired nominal value provide lesser performance. In the half-shaft example above, the engineering specification indicates a performance measure for which better performance is indicated by a minimum measured value. Accordingly, since the performance measure decreases as the feature size increases, the MAX value of the feature size is the desired nominal value. The desired nominal value may be indicated by a user or computed from the engineering specification given an indication of the desired performance measure.
The first step of computing the adjusted unit cost is receiving the manufacturing capability distribution and unit cost in step 150. A desired nominal value of the feature is then selected in step 152. Next, over a range of possible values for the other variables (two of the MIN, MAX and μ values), the manufacturing capability distribution is evaluated to obtain a value, but keeping μ between MIN and MAX (step 154), thus providing the adjusted unit cost 114. Typical shapes of an adjusted unit cost 114 are shown in FIGS. 12-14.
If the mean μ is a function of MIN and MAX, the distribution P of equation (2) is a function of one variable, using substitution, when one of MIN, MAX and μ is fixed. Thus P is a function of one variable (either MIN, MAX or μ) which is a feature size. The adjusted unit cost thus can be represented by the unit cost divided by the manufacturing capability distribution P as a function of one variable representing the feature size. For example, if MAX is the desired nominal size and μ=(MAX+MIN)/2, then P in equation (2) can be rewritten as:
P'=P Z< (MAX-(MAX+MIN)/2!/σ!-P Z< (MIN-(MAX+MIN)/2!/σ!(3)
Such an equation can be represented by a curve 126 in FIG. 12. This curve indicates that adjusted unit cost increases as the acceptable minimum feature size increases towards the desired nominal feature size. Similarly, a curve 127 in FIG. 13 represents the adjusted unit cost where the MIN value is the desired nominal feature value. This curve indicates that the adjusted cost increases as the acceptable maximum feature size decreases towards the desired nominal feature size. Finally, curves 128a and 128b illustrate the case where the mean μ is the desired nominal feature size. As the acceptable MIN and MAX values become closer to μ, adjusted unit cost increases. Curves 126, 127 and 128 can be continuous or contain singularities.
The adjusted unit cost 114 is input to a capability analyzer 116 along with the engineering specifications 100. The capability analyzer 116 determines, for a number of possible feature sizes, the probable performance according to the engineering specifications 100 and the adjusted unit cost for the feature size according to the adjusted unit cost information 114. For several selected feature sizes, an ordered pair of an adjusted unit cost and probable performance is obtained. These ordered pairs represent the manufacturers capability curve 118. A flowchart describing the operation of capability analyzer 116 is shown in FIG. 17.
Referring to FIG. 17, an initial feature size is selected in step 160. For example, the initial feature size may be the MIN or MAX value selected for the manufacturing capability distribution. The performance and adjusted unit cost for the selected feature size is determined in step 162 using the engineering specification 100 and the adjusted unit cost information 114. In particular, referring now to FIG. 10, using a selected feature size fo, a corresponding performance ko is selected. Similarly, referring now to FIG. 12, using a selected feature size fo, a corresponding adjusted unit cost value co is selected. The ordered pair (ko, co) of the selected performance and unit cost is then stored and/or displayed in step 164. The next feature size is selected in step 166 and steps 162 through 166 are repeated over the range of acceptable feature sizes. When complete, a graph representing the ordered pairs may be displayed and/or other operations like curve-fitting may be performed. For example, the performance value ko and adjusted unit cost co are displayed as indicated in FIG. 15.
A manufacturer's capability curve 118 is represented graphically for this example in FIG. 15 as shown at 120. Different curves may also be generated for different manufacturing standard deviations. For example, given the selection of a new manufacturing standard deviation for the manufacturers capability curve, an additional manufacturer's capability curve may be generated, such as indicated at 122 and 124. These other standard deviation values may be used to determine how much of an improvement should be made to the manufacturing process or how constraints on manufacturing may be relaxed and still maintain adequate performance from the product.
A display of a manufacturer's capability curve may also be used to assist in determining whether suitable performance can be achieved at an acceptable cost. In FIG. 15, an acceptable cost is indicated at 130, and a performance requirement as indicated at 132. These two values define a customer acceptance space 134. If the manufacturer's capability curve, as indicated at 120, does not fall within the customer's acceptance space, the given feature is a "StatKC" with respect to meeting the performance requirements of the product.
With this capability to correlate customer requirement to cost, a sensitivity analysis has been conducted to assess how improvements or degradations in manufacturing capability would affect a manufacturer's capability curves. Improvements could come from machine modifications, new machines, or machine parameter adjustments derived from design of experiments.
In the example shown above, the adjusted unit cost indicates the cost of manufacture. An additional factor of profit may be added to obtain an adjusted customer unit price. Additionally, the manufacturer's capability curves for a number of key characteristics may be combined to determine the manufacturer's adjusted unit cost for combinations of product features, or for the whole product.
Having now described a few embodiments of the invention, it should be apparent to those skilled in the art that the foregoing is merely illustrative and not limiting, having been presented by way of example only. Numerous modifications and other embodiments are within the scope of one of ordinary skill in the art and are contemplated as falling within the scope of the invention as defined by the appended claims and equivalents thereto.
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Holocaust In The Netherlands
Posted 22 October 2003 - 07:15 AM
Best to all the lil family,
Posted 22 November 2003 - 06:39 PM
Thanks for sharing this unforgettable and important piece of history with us. It reminded me of the book The Diary of Anne Frank, in which Anne describes all of the horrible acts and unbelieveable new laws that were inflicted upon the Jews in Holland in the early 1940's. It always makes me sad to read about the horrors of the Holocaust, but it's important to read about them and remember what the Jews went through.
Posted 19 February 2004 - 12:00 PM
Lest we forget.
Edited by Vicky, 19 February 2004 - 12:04 PM.
Posted 19 February 2004 - 02:53 PM
* We Shall Never Forget *
--Wild Lorie
Posted 19 February 2004 - 03:58 PM
if you have stories of your nice family to share, I hope we'll have the chance to read some of them.
With all my respect to them,
Posted 20 February 2004 - 05:17 PM
Thanks for the interest! I'll have to post them one day soon. Maybe tomorrow afternoon... as they are predicting a big rainstorm here and I'll be at home with a blanket and soup
--Wild Lorie
Posted 22 April 2004 - 09:13 AM
I am just reading this for the first time. Now I have a task today to read all of it It looks to be somevery interesting reading Thank you for the opportunity to learn & re-learn...Cindy
Posted 22 April 2004 - 07:07 PM
You did a great job Mark. It is quite sickening to read about the proliferation of laws and regulations against the Jews, especially when you know were it was ultimately going to lead. You wish you could travel back in time and warn them all. But like you said, where were they going to go to escape this?
Posted 10 June 2004 - 02:40 AM
Posted 23 June 2004 - 03:28 PM
I've found this thread most interesting and informative. My husband thinks I'm morbid, but I've read mounds of material regarding the Holocaust in the past several years. I just couldn't fathom how MILLIONS were systematically put to death because of their ethnicity. HOW? WHY? It truly boggles the mind....
One more thing: it should be remembered and commented on that many, many Dutch men and women risked, and indeed, lost their lives for hiding and trying to save Jews during the war. Two of my treasured books are Corrie ten Boom's "The Hiding Place", and Diet Eman's "Things We Couldn't Say" - here's a bit from the back cover:
Things We Couldn't Say is the inspiring true story of Diet Eman, a young Dutch woman who, with her fiance, Hein Sietsma, risked everything to rescue imperiled Jews in Nazi-occupied Holland during World War II. Throughout the years that Diet and Hein aided the Resistance-work that would cost Diet her freedom and Hein his life-their courageous effort ultimately saved the lives of hundreds of Dutch Jews. Possessing all the emotional impact of "The Diary of Anne Frank" and all the drama of "The Hiding Place", Diet Eman's "Things We Couldn't Say" is an unforgettable story of heroism, faith, and-above all-love.
This book is written in first person and is based on her diaries, letters to and from her fiance, and personal recollections. Absolutely fantastic, and backs up much of what Mark posted here........if anyone ever gets the chance to read it, prepare yourself with a box of tissues!
Regards to all!
Posted 24 June 2004 - 03:44 PM
However, you give me too much credit here. I edited the excerpts and added relevant information from other books and facts I learned from my wife Daphne and what I remember from history classes at school.
Reading about the Holocaust and posting in this topic has been part of my search for answers, mainly focused on why? Indeed it boggles the mind and I'm not done in my search yet, and I don't think I ever will.
Thank you for the suggestions of the two books, which I have not read yet. Another to read is "Om erger te voorkomen (To prevent the worse) by Nanda van der Zee and the books with personal experiences of Eli Asser. However, I don't know if these authors' books have been translated in English. That's for the Dutch part. I don't think I have to mention the work of Primo Levi to you.
Thanks again, Deanna.
Posted 25 June 2004 - 11:05 AM
Posted 29 June 2004 - 02:47 PM
It's quite revealing of how things went and how many Dutch people risked their own lives to save the lives of Jews by hiding them from the Germans.....
It's also a reminder of the horrors of the Holocaust.
Her story is one of the many ....
Quite a sad destiny ....
I've seen the movie just a few days ago and it moved me deeply.
Posted 29 June 2004 - 03:07 PM
"The Hiding Place" I've read this book just how many times.... a wonderful book,
Two of my treasured books are Corrie ten Boom's "The Hiding Place"
I was told about it by a friend of Brother Andrew, a Dutch missionary. Brought it with me all the way from Japan...my favourite. misako
Posted 29 June 2004 - 03:20 PM
Yes that's the one Misako.
"The Hiding Place" I've read this book just how many times.... a wonderful book,
I was told about it by a friend of Brother Andrew, a Dutch missionary. Brought it with me all the way from Japan...my favourite. misako
Really advise others too in reading the book and/or watching the movie.....
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text:
Ben Treece: State of the economyWritten by Ben Treece | | firstname.lastname@example.com
While presenting to members of a 401(k) plan that we advise in Auburn Hills, we were revisiting our economic forecasts from back in the first quarter of 2012 and found that many of our predictions came to fruition. We predicted we would begin to see signs of a strengthening economy, but that policy would hold back the private sector. Sure enough, failed policies from the federal, state and local levels have resulted in a temporary freeze in the economy.
Manufacturing, retail sales and housing prices and activity are all up in the reporting period, however hiring has leveled off and jobless claims have ticked up slightly. Unemployment has continued to be an issue during this recovery for two main reasons: We lack skilled labor and future employee costs are unknown.
The markets and public policy have a very close relationship; one tends to mold the other. The fact of the matter is that the Affordable Care Act has many employers terrified to take on new staff. This is not a comment on socialized medicine, the current administration or the health care industry, this is simply commenting on documented responses of business owners to the law as it is written. If the Affordable Care Act carries on as is, expect unemployment to remain high for an extended period of time.
Private sector business owners have also noticed a frightening trend when hiring; finding skilled workers has proven to be very difficult. Between younger generations' lack of interest in engineering studies and many apprenticeship training programs closing their doors, finding the right people for the manufacturing jobs that have been moving back from overseas has not been an easy task.
"Onshoring" of manufacturing jobs is another trend that we predicted well over a year ago. Between rising labor costs abroad and the inability to protect product patents, many manufacturers have decided to shift their factories to North America (Bose and Honda are two big ones).
Adding to the solid economic numbers, "industrial production" was up 0.6 percent year over year and "home builder confidence" turned in at the highest level since February of 2007. This shows us that the bottom of the real estate market has likely come and gone, and buyers are now looking for new construction homes instead of older model homes from the '40s, '50s and '60s.
One cause for our concerns has been an increase in food, energy and housing costs, or what is known in economics as inelastic goods. These are items that even when the price increases, their demand stays relatively constant. When prices increase for inelastic goods, consumers have fewer dollars to allocate towards discretionary spending, e.g., entertainment. Historically, when these prices increase and the economy fails to grow, we have what is called stagflation, a term tightly associated with the "misery index" under President Jimmy Carter.
On the whole, the economy is improving, slowly but surely. In our opinion there are many policy choices that could be made to speed up the recovery, but all things considered the U.S. economy is getting stronger, even if the numbers do not always reflect it.
In my Aug. 12 column, "Corn is king," I quoted the price of corn as being $800/bushel. Corn is quoted in cents, not dollars. The current price of corn is just over 800 cents/bushel, or $8/bushel. I would like to thank my readers for pointing out my mistake in a courteous and professional manner.
Ben Treece is a 2009 Graduate from the University of Miami (FL), BBA international finance and marketing. He is a partner with Treece Investment Advisory Corp. (www.TreeceInvestments.com) and a stockbroker licensed with FINRA, working for Treece Financial Services Corp.
Tags: Ben Treece, Treece Blog


text:
This is $22 less than the next reputable vendor and one of the lowest prices we have seen for this GPS.
Features 5" touchscreen display, NAVTEQ maps of North America, lane guidance, Text To Speech, bluetooth for hands-free calling, Lifetime Map & Traffic Updates, and MicroSD card input. Also has automatic destination sorting to provide the most efficient route between many points of interest.


text: Kyle Grimm, based in Cadwalader's New York office, focuses his practice primarily in the areas of complex commercial and corporate litigation. Kyle has written on a range of topics including standing doctrine, administrative rulemakings, environmental regulation, and the use of wiretap evidence in white-collar prosecutions. Some of his published work includes "Endangerment" of the Common Law: Do Rulemakings as to Greenhouse Gases Under the Clean Air Act Displace Federal Common-Law Claims for the Public Nuisance of Global Warming?, 41 Seton Hall L. Rev. 671 (2011) and The Expanded Use of Wiretap Evidence in White-Collar Prosecutions: Rebalancing Privacy Through More Vigorous Enforcement of the Predicate Offense Requirement and the Suppression Provisions of Title III, Pace Law Review (forthcoming Fall 2013). Kyle also maintains an active pro bono practice. Before joining Cadwalader, Kyle served as a law clerk for United States District Judge Anne E. Thompson (D.N.J.). He received his law degree, summa cum laude and Order of the Coif, from Seton Hall University School of Law, where he was both a Chancellor's Scholar and the Thomas J. Brandle Scholar. While in law school, Kyle served on the editorial board of the Seton Hall Law Review. He is admitted to practice in the State of New York. News & ResourcesNEWSRESOURCESClients & Friends Memos• U.S. Federal Estate, Gift and Generation Skipping Transfer ("GST") Taxes Jan 29, 2010


text:
Speed cameras will stay in Gloucestershire - but no more maintenance
Posted: August 03, 2010|
SPEED cameras in Gloucestershire will not be switched off – but highway bosses say maintenance will become less frequent.
As Oxfordshire's speed cameras were turned off to save cash, Gloucestershire County Council confirmed the county's 28 cameras would remain in action.
The cameras were due to be updated to a new digital format, but after cuts of £7million were imposed by the coalition Government, the council was forced to abandon the plan.
Now, the cameras will carry on flashing speeding motorists – but the films may not be changed as often as before.
Mark Hawthorne, leader of the council, said no new investment in speed cameras will save more than £300,000.
"We have had to make decisions about where we make savings," he said.
"From now on there will be no new investment in speed cameras in Gloucestershire and a review of how camera enforcement operates is planned. This will save £363,000 this year. The existing network will continue to operate but cameras will be refilled less frequently."
The decision by councils across the UK and central Government to slash funding for the controversial devices has been slammed by road safety campaigners nationwide.
Kate Tucker, of Wotton-under-Edge, has spent many years campaigning for safer roads following the death of her husband Ken Delaney, 44, in Claypits, near Eastington, in 2002.
Kate said: "I think they should keep the cameras going as long as possible in Gloucestershire.
"I'll say what I've said before, I think they're useful and I think they do save lives, so I think they should maintain them as long as they can."
Under the terms of the new budget, the road safety grant for 2010 to 2011 has been slashed by 40 per cent.
Crucially, the capital grant – a £17.2million annual fund that typically pays for the cameras – has also been abolished in the budget.
With few other ways of funding the cameras – as the fines from speeding go to the Treasury – councils would have to pay using revenue earmarked for schools and other projects.
In the case of Oxfordshire, the county council axed its £600,000 grant to the Thames Valley Safer Roads Partnership in a bid to find £1million in savings.


text:
Ever since August, residents of the historic Ansonborough neighborhood have been able to listen and set their clocks: Construction workers rebuilding the Gaillard Auditorium arrive at 5 a.m.
Now they face the possibility that construction will continue past the present 7 p.m. quitting time until 1 a.m., leaving neighbors just four quiet hours for sleeping.
You can understand why those neighbors are frustrated. They are being told that the extra shift might be necessary for SKANSKA to finish work on schedule for a January 2015 opening. But neighbors don't hear anybody expressing concern that they are bearing an unfair burden so that the company can finish on a schedule that it, wisely or not, agreed upon.
Steve Hanson, immediate past president of the Historic Ansonborough Neighborhood Association, said about 30 members showed up at a meeting called by SKANSKA Monday night to keep neighbors up to date. Mr. Hanson fears that while SKANSKA is saying the late-night work is only a possibility, it is actually imminent. Indeed, the company has said it might start as early as Monday. The company will give neighbors 48 hours notice if they do add the late-night shift.
The noisy, dusty demolition of the old auditorium was a warning sign to neighbors. Even now that construction is under way, residents awake six days a week to the roar of trucks and to the sound of workers' boom boxes.
When Buist School, across the street from the auditorium, and the Gaillard were both under construction at the same time, the noise was doubly problematic.
Now a safety problem has emerged that probably shouldn't have been a surprise to experienced contractors. It is not safe for workers to pour concrete while others are doing steel work above them. Work that SKANSKA planned to do concurrently must be done consecutively.
The construction team says that large trucks mixing concrete and crews assembling steel structures will be finished by 8 p.m., and that work after then will be quiet — mostly shaping concrete.
But neighbors are skeptical. They have had to deal with unexpected air emissions, traffic and noise. The idea of extending construction until 1 a.m. — even just concrete smoothing — isn't sitting well.
Ansonborough residents say they understand that delays in construction can be costly. They understand that the city wants to move employees into offices at the auditorium and stop paying for leases elsewhere. They understand that the sooner the auditorium is available for use, the better the bottom line.
But they also believe that they have a right to reside comfortably in their homes — and get more than four hours of sleep a night.
Surely the city and SKANSKA, the company that built the new Cooper River bridge, can do their work and respect the neighborhood at the same time.
In no way can they expect people to be satisfied while living adjacent to a major construction project that operates 20 hours a day, six days a week.
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text:
Podcast (seems-like-god-reflections): Play in new window | Download (Duration: 3:28 — 4.0MB)
The lost sheep parable is similar to the woman and the lost coin, which I used in the last Daily Progress post. At least in so much as it talks about "rejoicing" when we act in harmony with Theos and Creation.
Unlike the coin, however, the sheep has the ability to act on its own. It may be tangled in brush, or stuck in a narrow place in the rocks. But it can turn around; it can pull away from the undergrowth.
We, like the sheep, can make choices.
Today, may we make good ones.
And we will all rejoice.
Which one of you, having a hundred sheep and losing one of them, does not leave the ninety-nine in the wilderness and go after the one that is lost until he finds it? When he has found it, he lays it on his shoulders and rejoices. And when he comes home, he calls together his friends and neighbours, saying to them, "Rejoice with me, for I have found my sheep that was lost." Luke 15:4-6


text:
Perfect your knowledge of Pro Tools 10 with this CD/DVD combo.
PRO TOOLS 10 ADVANCED MUSIC PRODUCTION TECHNIQUES is the official Avid Learning Series Expert Level guide to the advanced operation of Pro Tools in a professional music production environment. It includes technical insight into both Pro Tools HD and HDX hardware and software, common workflows, and advanced editing and mixing topics. The materials on the supplemental DVD—sample sessions and source files used in the book's many exercises and projects—help to reinforce the skills being learned. Whether you're learning on your own or pursuing formal Pro Tools certification through an Avid Learning Partner, PRO TOOLS 10 ADVANCED MUSIC PRODUCTION TECHNIQUES will help you achieve expert-level mastery of Pro Tools. PRO TOOLS 10 ADVANCED MUSIC PRODUCTION TECHNIQUES (Course 310M) is part of the Avid Learning Series. This course leads to expert-level certification.
About the author:
Robert Campbell
Robert Campbell has held numerous positions in the professional audio community, including musician, instructor, and audio engineer. But it was his tenure with Digidesign as a Product Manager where he made his mark in the audio industry. Rob was the product manager behind such groundbreaking products as Pro Tools HD, Mbox, and Digi 002, to name a few. After leaving Digidesign, Rob was the chief instructor at several Pro Tools training facilities, an instructor at San Francisco State University, and continues to serve as a consultant for Avid. He has personally instructed thousands of students from beginners to working professionals as a certified Master Instructor on Pro Tools, ICON, and VENUE. Rob has authored several Avid certified courses such as Pro Tools 201, ICON, and VENUE courses.


text:
The Senate on Wednesday voted down House Budget Chairman Paul Ryan's controversial budget blueprint, 57 to 40, in a Democratic effort to win advantage in continuing deficit talks and in the 2012 election season.
The vote marked an effort by Democrats to exploit public opposition to the Wisconsin Republican's plan to shift Medicare to a subsidy system. A special election in New York's 26th Congressional District on Tuesday, won by a Democratic underdog, became something of a referendum on the Ryan plan, and Democrats see opposition to it as a potent political weapon in 2012.
Still, it is unclear how much voting in support of the plan will bother Senate Republicans going forward. Some polls show efforts to sell the Ryan plan as an effort to save Medicare from fiscal collapse can succeed with voters. And Republicans who might be hurt in the next year's elections by backing the plan—Sens. Scott Brown, R-Mass., and Olympia Snowe, R-Maine, opposed it.
Sen. Richard Lugar, R-Ind., who is up for reelection in 2012, backed the plan, but Lugar's main challenge is the GOP primary. Many observers think he will retire or fail to gain the GOP nomination in any event. Sen. Dean Heller, R-Nev., newly appointed from the House to replace Sen. John Ensign, R-Nev., on Wednesday cast his second vote for the plan, which Democrats will work to exploit in Heller's 2012 race.
Democrats have yet to offer their fiscal 2012 budget resolution. In forcing a vote on Ryan's plan, Senate Majority Leader Harry Reid, D-Nev., took what Republicans called an unprecedented step of forcing a vote on a budget that he opposes without offering one he supports. The maneuver highlighted Senate Democrats' decision to mostly abandon an affirmative legislative agenda and instead highlight opposition to GOP plans. Democrats can argue they are acting out of necessity because they cannot pass—in either the Senate or the House—most of their preferred legislation.
"This is a complete and total abdication of their responsibilities," Senate Minority Leader Mitch McConnell, R-Ky., said. "And there is no excuse for it. We have an obligation to come up with a plan. Democrats are officially abdicating that responsibility this week."
The Senate was also set to vote on President Obama's original fiscal 2012 budget plan, on a budget resolution by Senate Budget ranking member Jeff Sessions, R-Ala., then on an alternative budget resolution by Sens. Rand Paul, R-Ky., and Pat Toomey, R-Pa. All of the budgets were expected to fall short of the 51 votes needed to start consideration of the bill under budget rules.
Democrats hope the votes will demonstrate that House Republicans must compromise to reach a deficit deal and raise the $14.3 trillion debt ceiling, making it easer to cut a deal in ongoing talks led by Vice President Joe Biden.


text:
A judge Friday morning in Charleston County court denied an attempt to further lower bail for the Mount Pleasant man accused of killing a man in a King Street brawl.
Dalton Ellis Clarke, 24, has been in jail since his May arrest in connection to the death of Clinton Seymour, 27.
Seymour died April 28 at the Medical University Hospital while being treated for skull fractures that resulted from being "sucker-punched" during the brawl. A joke prompted the fatal fight, Charleston police said.
Clarke's bail was initially set at $500,000 for an involuntary manslaughter charge. A magistrate judge reduced the amount to $150,000 two weeks ago during a preliminary hearing.
In court on Friday, Clarke's attorney Michael DuPree unsuccessfully urged 9th Circuit Judge Roger Young to lower bail again to $25,000.
"This case could take some time to go to trial. I'd hate to see (Clarke) sitting in jail until then," DuPree said.
Evidence painting Clarke as Seymour's killer was thin, DuPree told Young, considering investigators initially charged another man in the death. Authorities only targeted Clarke after a few text messages and witness stories surfaced saying he was the one who threw the "sucker punch" that ended Seymour's life, DuPree argued.
Ninth Circuit Assistant Solicitor Chad Simpson told the judge at least six different people have identified Clarke as Seymour's killer.
A "silly, verbal only dispute" between Seymour's friends and Clarke's turned violent when Clarke "sprinted up and punched the first guy he saw," Simpson said.
That person happened to be Seymour, causing him to fall to the ground, striking his head against the concrete.
Seymour had been the sober designated driver for his group. He wasn't even involved in the initial argument, Simpson alleged.
"Sucker-punched is a very accurate description of what happened here," he said.
Seymour's father, Don Seymour addressed the court, insisting that Clarke would be a danger to the community if released from jail.
"Clint, in essence, is the community. ... Law-abiding, sober citizens ought to be able to walk the streets of this city without the risk of their lives ending instantly for no reason," Don Seymour said.
At the hearing's conclusion, Young decided against lowering bail. If Clarke does get out of jail, Young added, he will be subjected to GPS monitoring restricting him to home, work and church.
Reach Christina Elmore at 937-5908 or at Twitter.com/celmorePC.
- Keywords
Notice about comments:
The Post and Courier is pleased to offer readers the enhanced ability to comment on stories. Some of the comments may be reprinted elsewhere in the site or in the newspaper. We ask that you refrain from profanity, hate speech, personal comments and remarks that are off point.
We do not edit user submitted statements and we cannot promise that readers will not occasionally find offensive or inaccurate comments posted in the comments area. If you find a comment that is objectionable, please click the X that appears in the upper right corner when you hover over a comment. This will send the comment to Facebook for review. Please be reminded, however, that in accordance with our Terms of Use and federal law, we are under no obligation to remove any third party comments posted on our website. Read our full terms and conditions.


text:
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