The New Quality Tools


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The New Quality Tools

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The New Quality Tools

  1. 1. The 'New' Tools The following table displays the list of the so-called 'new' Japanese tools. These tools have been in widespread use in Japan since the mid-1970s. It is some measure of America's devotion to quality that these tools have only become of interest to American business in the 1980s and 1990s. The tools described are only a few among those that can be potentially developed. In fact, it is likely that many more tools are currently in use in Japan but not known in America! The term 'new' tools was used in Japan as the tools were first employed. More recently (Brassard, 1989) these tools have been renamed as the Management and Planning (MP) tools. The designation 'new' is retained in this document since it is more widely used than the 'MP' term. Tool Name Utilization Affinity Diagram Used to Organize abstract thinking about a problem. Relations Diagram Used for determining causalities among parts of a problem. Systematic Diagram Planning tool. Matrix Diagram (many types) Used to organize knowledge in a matrix format; sometimes includes intercell relationships. Matrix Data Analysis Method Principal components technique is performed on matrix data. Process Decision Program Chart (PDPC) Determining which processes to use by evaluating events and prospective outcomes. Arrow Diagram Used to do 'what-iffing' on flow of process. The tools listed in table above provide a relatively complete capability of analyzing and understanding a problem. While not essential, the tools can be used in the order shown from top to bottom of the table to move from more abstract analysis (affinity) to the explicit detail provided by the arrow diagram. These tools can be usefully combined with the 7 standard tools (see discussion at end of chapter). Table of Contents • Affinity Diagrams • Relations Diagrams • Systematic Diagrams • Matrix-Related Tools • Process Decision Program Chart
  2. 2. • Arrow Diagrams • Other Japanese-Origin Tools Affinity Diagrams (KJ Method) The affinity diagram tool is also known as the KJ method from the name of the inventor, Kawakita Jiro (note: Japanese reverse their names, usually writing the surname first). An affinity diagram is useful for brainstorming about various possibilities about how to solve a difficult problem or when a team cannot clearly decide what to do next. Figure 2.11 shows an example of the structure of an affinity diagram. The name of the problem considered is displayed at the top of the diagram and subproblems are grouped internal to the main problem. The basic idea is for the team to suggest, at random, areas of concern, then arrange these concerns in groupings and name the groupings. One way of manually conducting an affinity diagram session is to write areas of concern on post-it notes, then place the notes on a large board and have team members discuss and arrange the notes into groupings. The benefit from the technique, like all the tools, is the enhanced visualization of the problem that the use of the tool provides. In the example given in the figure below, there are shown four grouped problem areas that contribute to the main problem. Also shown are three subproblems within the problem designated in the problem area at the upper right of the diagram. Using the Affinity Diagram as a Team
  3. 3. It is relatively simple to try out using affinity diagrams yourself using the post-it note method mentioned above. Use the steps shown below. 1. Gather a team; make sure the right people are on the team - that is that the team has common goals and interests. 2. Discuss and select a specific problem area. For example, lack of productivity. 3. Have each member jot down as many contributing factors to the selected problem as possible on a post-it note. 4. Post the note on a board and begin as a team to logically group the notes. 5. Name the logically selected groups. 6. Have a period of quiet reflection and permitting any team member to move any note to any other desired group. 7. Discuss the changes. Iterate these last two steps until a steady state is reached. 8. Next, analyze the different groupings and decide which things to focus on in the remaining tools. This another example used by a shipping company. The affinity diagram can be improved by computer automation. Techniques for computerization are discussed in a subsequent chapter.
  4. 4. Relations Diagrams Relations diagrams specify the relationships among things. More specifically, these diagrams are used to map and analyze problems where causes of the problem have complex interrelationships. In contrast to the Ishikawa diagram in which all causes of a problem are assumed to be hierarchically decomposable, the relations diagram promotes discovery of relationship among causes. In plain terms, this means that a single thing might influence two or more other things, a situation that cannot be easily shown in a fishbone diagram. Consider the figure below in which multiple relationships among causes of a specific problem are shown. When teams work in a group to create relation diagrams, the 'card' or 'post-it note' technique can be used in which causes are specified by team members and arranged on a table or board and arrows drawn between cards or notes as needed to show the relationships. The figure below shows how relations diagrams and Ishikawa diagrams are related. Ishikawa diagrams are arranged hierarchically, that is, there is a main node, subnodes, and subnodes of the subnodes, and so forth. The arrangement in which no branches are permitted to crossover is called a strict hierarchy; those cases in which crossover is permitted is termed a tangled hierarchy. The relations diagram is most like a tangled hierarchy. Crossover is permitted, in fact, encouraged. The relations diagram and the Ishikawa diagram are identical if the structure of either graph does not permit crossovers between the hierarchically organized structures. In Figure 2.12, the top diagram shows a simple Ishikawa diagram with 6 causes shown (Cn). Shown below the Ishikawa diagram is the identical relations diagram with one additional link, shown to the left. Note that the primary difference between the two diagrams is
  5. 5. simply the arrangement of the drawing - and the ability to have additional interconnectivity between causes. In truth, there is no reason that such interconnectivity cannot be shown on the fishbone. Systematic Diagram Systematic diagrams help teams or individuals think systematically about how to achieve a goal. Affinity diagrams assist in identifying a problem, relations diagrams help to figure out what is related to a problem, and systematic diagrams organize the aspects of the solution of the problem. Figure 2.12 shows a general form of a systematic diagram, in this case a structure for assisting in breaking a goal down into subgoals. Subgoals in this case can become sets of methods and plans which assist in achieving the subsequent goal. Another way to use the systematic diagram is to decompose components or physical processes into their subparts. This type of hierarchy is sometimes known as a whole-part hierarchy, in reference to breaking the whole into it's constituent parts. The term systematic diagram is also referred to, by some, as the tree diagram due to the way that the diagram appears. Once the systematic diagram is organized and completed, the tip nodes (those to the right in the figure) represent the specific methods and actions that are to be taken. In this configuration, one can use a matrix diagram to prioritize and organize the work to be done. When a matrix diagram is used in this fashion it is sometimes termed a prioritization matrix.
  6. 6. Matrix-Related Tools Matrix diagrams permit organization of knowledge so that relationships between factors, causes, objectives, (or any thing that one wants to show) can be shown. Matrices, of course, provide rows and columns with intersecting cells that can be filled with information that describes the relation between the items located in the rows and columns. Several basic forms of matrix- related tools have been developed including, an L-type matrix, a T-type matrix, Y-type matrices, and X-type matrices. The L-type matrix is just a two dimensional table that places contrasting elements in the rows and columns of the matrix. The L term is used to describe the upside-down shape of the labels of the row and columns. The T-type matrix forms the labels in the form of a T adding an additional matrix above the top of the matrix. X and Y-type matrices are simply composed of multiple L and T matrices. As shown in the diagram below, the L is discernable in the column and row labeled Cn and Rn; for the T the additional set of Cns gives the appearance of a T. The 'L' R1 R2 R3 R4 L1 1 2 3 4 L2 1 2 3 4 L3 1 2 3 4 L4 1 2 3 4 The 'T' L4 1 2 3 4 L3 1 2 3 4 L2 1 2 3 4 L1 1 2 3 4 R1 R2 R3 R4 L1 1 2 3 4 L2 1 2 3 4 L3 1 2 3 4 L4 1 2 3 4 The next figure shows another matrix style display technique with a 'rooftop' on the top of the matrix. This addition makes the diagram into what is sometimes called the "House of Quality." The additional diagram provides the capability of making additional relationships between factors that are listed in the columns.
  7. 7. The typical means for showing relationship in a matrix diagram is to place a symbol in a cell in the matrix, for example: - strong relationship - relationship - possible relationship Naturally, it is plausible to use any type of symbol that has meaning to the user. Different types of symbols are used by different authors and software manufacturers of matrix toolsets. One popular methodology based on matrix-style representations is known as Quality Function Deployment (QFD). QFD designates the columns as hows and the rows as whats, that is, how to accomplish something and what to accomplish. The whats are customer requirements or objectives; the hows are the different things that can be done to achieve the objectives. The roof of the hows show any interrelationship among the hows. In one software package by Qualisoft (1991), the whats are segmented into different types of requirements and the hows into different categories of things to be accomplished. To use this system, the user places in cells various symbols indicating the relationships between the whats and hows. Weights indicating
  8. 8. the relative importance of the whats permit assessment of which of the columns (hows) provide the most benefit. Matrices and Principal Components Analysis. One of the seven 'new' tools described by Mizuno (1979) is Matrix Data Analysis, a technique which creates correlation matrices for preferences of individuals for a product. Brassard (1989) drops this tool from the list of new tools, indicating that the tool is too complex for inclusion in this set of tools. The technique employs an analysis of the correlation matrix that is analyzed by principal components methods. In principal components, information is extracted from the matrix that shows how much each feature contributes to the principal factors which account for the variance in the matrix. Vectors of composite preferences then give a perspective on the characteristics for particular items in the correlation matrix, which can be used for decision making about which features to include or not include in a product. This technique is quite similar to the analytical hierarchy process (described below) for general decision making. The fundamental methodology is to convert the matrix of information about interrelationships between variables into a simpler form that creates a set of eigenvectors which are made up from a sum of fractions of the contributing features. By scanning which features are included, an assessment can be made about the relative importance of each feature to the overall preference matrix. Process Decision Program Chart (PDPC) Process decision program charts are charts that help the user select the best processes to be used to accomplish a desired task. While the method has many variations, the most simple explanation of the method is that one shows the possible tasks in a process and the task sequences of all the relevant alternatives. For example, this figure shows starting at some beginning point and proceeding toward a goal. Each circle (node) is a separate task. In this figure, four different pathways are possible from start to goal. The fundamental idea is that the goal can be reached in various ways; however, only one of the sequence of tasks will be optimal. The PDPC assists in visualizing the alternatives when planning a sequence of tasks in a process. Two major alternatives for analyzing PDPCs are used - forward planning and backward planning. The first type is illustrated in the figure to the right and the latter in figure below. The method in forward planning is to begin at the start node and work toward the goal node, attempting to select the best path as one moves forward. In contrast, backward planning starts at the end node and moves toward the start.
  9. 9. Arrow Diagrams Arrow diagrams display information about the operation of a process by using arrows and nodes. Arrow diagrams can be thought of as a way to understand the operation of a process using time, cost, or other metrics. As a simple example, consider the figure below which displays a simplified process of creating a new product. In this very simple diagram, two paths are shown, the top path for creating the hardware component of the product and the bottom path, the software component. Each link (i.e., arrow) has a numerical label on it which designates the time required to proceed from one node to the next. In this example, the values used for the arrows are in weeks. Hence, the time required for completing the initial software for this product is much longer than the time required for the hardware. The arrow diagram, as in all the other tools, simply permits an explicit visualization of the bottleneck problem that will occur in this process! Gantt charts have been used for many years to permit visualization and scheduling of parallel activities. The figure below shows a typical Gantt chart. Tasks are listed on
  10. 10. the right side of the diagram. The times during which the tasks are scheduled are shown by the extent of the arrow in the diagram. The abscissa in this example might be weeks or months. In contrast, the arrow diagram attaches the name of each task to a node and shows the times between the tasks. Parallelism is easily seen and, moreover, disconnects in time are easily observed so that delays can be identified and plans can be altered to achieve the minimum time from start to completion of the process. Note that the same type of analysis could be accomplished using cost or any other metric that is appropriate to the process. Other Japanese-Origin Tools There are undoubtedly many other Japanese-origin and related tools than the ones discussed above. Two more that have gained prominence are the poke-yoke methodologies and the Taguchi methods. These two tools are briefly discussed next. Poke-Yoke. The term poke-yoke is a hybrid word created by Japanese manufacturing engineer Shigeo Shingo. The word comes from the words yokeru - (to avoid) and poka (inadvertent errors). Hence, the combination word means avoiding inadvertent errors. The term can be further anglicized as mistake-proofing, that is, making it impossible to do a task incorrectly. The text (NKS/factory magazine) referenced at the end of this chapter contains many examples of mistake-proofing. It is a very, very simple concept, yet not widely used. For example, if one part fits into a hole and it must fit in only one orientation, then fool-proofing the assembly of the parts requires that the part fit in the hole in only the correct orientation. This assembly constraint can be implemented, for example, by placing a small extrusion on the side of the inserted part that matches with a key on the part in which the first part is inserted. There are many examples of this type which can be found in processing, assembly, measurement, and other tasks. Human workers will make mistakes if it is possible. Poke-yoke simply removes the possibility.
  11. 11. Taguchi. Dr. Genichi Taguchi, a statistician, has become well-known for his method for assessing quality. Taguchi defines quality in terms of a loss function which assesses the loss to society for not having a high quality product. Hence, the higher the quality of the product, the lower the loss. The basic idea is that variables which influence a product can be varied to determine the performance of the product in various situations. In what might be thought of as a poor man's statistical design, the Taguchi method assesses variation in a matrix formulation which varies each significant variable around an operating point, keeping track of the products output for each variation captured in the matrix. A homely example will help explain. Consider a simple electronic circuit made up of several resistors and transistors, perhaps an amplifier. Each one of the components in the circuit when varied slightly can effect the gain of an amplifier. Taguchi's method essentially systematically varies the values of the circuit components, permitting the experimenter to see what effect variations will have on the performance of the electronic circuit. In short, the technique is an empirical means of determining exactly how a product will work and what variation it is likely to present.