Browse by Chapter. Browse by Resource. Facilities Planning by Tompkins 4th facilities planning tompkins 4th edition facilities planning tompkins 4th edition solutions at greenbookee.
File type: PDF. Tompkins, John A. White test bank solution manual exam bank facilities planning, 4th edition Facilities Planning, 4th Edition When it comes to facilities planning, engineers turn to this book to explore the most current practices. White, Yavuz A. The overall preference is thus c over b , which are both preferred over a. There are three components in an automatic factory — manufacturing, material handling, and the information system.
In terms of manufacturing, some decisive factors to justify automation are: Volume of production. Economics of scale can be achieved by mass production and the financial benefit can compensate the high capital cost of an automatic factory. Expensive machinery. Some industries, such as semiconductor, require expensive machinery. By automating, these machines can be fully utilized to reduce production cost.
Variability reduction. Manual machining, while still within tolerance, often produce parts with high variability. This variability can be reduced significantly by automation.
From a material handling perspective, automation is desirable to reduce cost in time due to savings in labor cost. In addition to cost saving, some product may require careful handling; therefore automation is an alternative to prevent product damage. In addition, the declining costs of computing and data storage continue to fuel the desire to invest in automation. Machinery for semiconductor production cost dearly and should be fully utilized. Product value is also very high; material-handling automation is needed to avert damage.
Another sector would be continuous flow manufacturing such as chemical products. User interface and training Obsolescence Lack of flexibility Risk of having all eggs in one basket if a disaster should strike the warehouse Answers to Problems at the End of Chapter 8 8. A list that is required for a fully automated cross docking facility with respect to the material handling aspect: Software for warehouse management.
Automatic material transport equipment for moving the materials. For example: conveyors, racks that are designed to accommodate cross docking facility, i. Industrial vehicles for transporting from the dock to storage or storage to dock.
This device will allow automated retrieval of loads from truck. This device will allow automated retrieval of loads from dock. Material handling device used Spacing between workstations buffer size 8.
The student may also come up with other types of systems. Instead of using AGVs, conveyors can be used for transporting materials. When using conveyors, a spine layout can also be implemented. When using a spine layout, there is no more loop around the system.
This trend is perpetuated by limited tool magazine size and more importantly; keeping a complete set of tools in a magazine may not be economically feasible since tools are generally expensive. Tools can be categorized into two types: resident, which reside in a machine permanently and transient, which is shared among machines and kept in central tool storage.
Determining how many resident and transient tools is the problem. This also translates to how to allocate the transient tools among machines and how many transport devices is needed. Given the machining schedule, usually based on order priority, the required tool sequence can be known. Simulation or integer programming can be used to find the optimal solution. In practice, keeping active inventory of all tools in the cell with their size, type, number and location, improving tool forecasts and warnings of tools changes, reducing delays in the system, and improving tool information reliability are the core of a tool management system.
Tools are still separated into resident tools and transient tools; however the proportion of resident tools is considerably higher than in a FMS setting. This can be attributed to the nature of SSMS where part only visit a machine once; thus more resident tools are needed.
This arrangement is more costly; in return it offers more versatility, more machine utilization, easier part scheduling and higher throughput. Answers to Problems at the End of Chapter 8 The handling device needs to be flexible in the sense that it must be able to handle all of the part types produced within the flexible cell. The WIP storage must also conform to the limitations of the cell and material handling system design.
In addition, the manual handling that would normally be involved moving a part from a storage device e. Therefore, each of the rules-of-thumb are satisfied in at least one way. Therefore, a worker may save time to perform the task, thus opening the worker to handling more machines. In addition, the operator will not have to spend time arranging components. Therefore, at least 4 of the 7 wastes are reduced. Both strive for eliminating or minimize waste, produce only what is demanded, minimize the use of time and space resources, and manufacture in the shortest cycle time possible.
Mass production is still the best process to use for high volume, repetitive products. JIT may also be difficult to Answers to Problems at the End of Chapter 8 implement to very low volume or unique products such as in a job shop environment unless there is flexibility in reordering the machine.
Like discrete-part production systems, a continuous production system starts with a batch that is processed; however, the batch is processed in a continuous manner from process to process. So, the batch size can be determined by the actual demand, and therefore, be thought of as a pull system. By limiting the size of the batch the WIP is naturally limited in the system as well.
However, it should be noted that most continuous production systems are used in very large scale production, so reducing batch sizes may reduce the utilization of the system. Response will be based on the paper chosen for review. In a U line balancing problem, the set of assignable task is enlarge by those tasks whose successors have been assigned, therefore U line balancing problem is more complex since now task grouping not only move in forward or backward direction as in a straight line, but it can also move in both directions at the same time.
In practice, rebalancing of the line is done quite often following demand changes. Rebalancing involves adding or removing machine from on the line or changing the standard time bases on new layout configuration; it also involves determining the number of operators required and assigning the machines that each operator tends.
The workers should be cross-trained so they can fix each others mistakes or aide in the quality resolution process. There would be cases of overlap, where the one worker would obstruct the path of another worker. Answers to Problems at the End of Chapter 8 8. The assignments are as follows: Processes Worker Assigned 1 1, 2, 3, 10 2 4, 5 3 6, 7, 8, 9 In this case each worker is not obstructed by any other worker; therefore, it would be a preferable arrangement compared with that of the solution to Problem 8.
A good roof design will also help thermal performance. A membrane layer to prevent water penetration, an insulation layer to assist with thermal comfort, and a vapor check to stop vapor migration are all requirements of a good roof.
The floor should have integral water-proofing and an applied membrane to seal the floor against water migration. The primary purpose of an enclosure system for a manufacturing facility is to keep out undesirables. The CU is approximately 0. Using Equation 9. If there are 2 lamps per luminary, then luminaries are required for the facility. This will allow luminaries to be placed within the facility. This result changes the coefficient of utilization in Table 9.
This result yields luminaries that can be placed within the facility. From Equation 9. The ECR is determined by examining Table 9. Since the ECR changed, this affects the coefficient of utilization slightly. The CU decreases to 0. As in Problem 9. This changes the value of the CU to 0. There are 20 classifications or groups of buildings governed by the UBC. Safety of regular building occupants 2. Safety of firefighters 3. Salvage of the building 4. The goods and equipment in the building 9.
Answers to Problems at the End of Chapter 9 9. Any point on the defined line segment is an optimum location. Any point in the defined square is an optimum location. Note: the vertical line from 6,10 to 6,12 is not supposed to be present.
This was an error that was created in production that was not caught during the editing process. Show below are plots of the cumulative weights along each axis. Answers to Problems at the End of Chapter 10 For the example, an optimal location was obtained. Building 1 is inside the contour line and Building 3 is outside the contour line.
The least cost location is Building 1: 20, All points on the straight line connecting 30,16 and 35,21 are optimal solutions, as confirmed by an exact solution procedure not included in the text.
Enumerating the unweighted maximum rectilinear distance for each of the three feasible locations gives: Decision Variables Obj. Note: solving for the unconstrained optimum location gives any point on the line segment connecting 25,15 and 30,10 for a maximum unweighted distance of Both locations coincide with an existing facility location. Machine i 1 2 3 4 5 Coordinates ai bi 10 25 10 15 15 30 20 10 25 25 Squared Difference Distance 2 2 x 1 - x 2 y 1 - y 2 d X 1,X2 0 We also compute the slopes of contour lines in the grid squares adjacent to the optimum location.
In so doing, we find that 1. Hence, the optimum minimax location is any point on the line segment connecting the 2. Using the half-sum method, half of the sum of the weights equals 7.
In general, we would need to consider each floor and, then, determine which floor yielded the minimum maximum weighted distance traveled. However, because the unconstrained optimum z-coordinate is What if the mail room is located in the basement? Twenty percent is between the new machine and each of the existing machines at 40, 0 and 0, Existing machine locations are dock locations, the percentages represent the movement between a dock and the storage location for an item, and the contour line is a continuous representation of the storage boundary for the item.
See Figure 7. This is knows as the Majority Theorem. Here, the four existing facilities form a quadrilateral. The half-sum method can be used.
Or, since one existing facility has a weight that is greater than half the total, by the Majority Theorem, it will be the optimum location. Magisterial District 1 2 3 4 5 6 7 8 9 10 Potential Sites 1 2 4 0 0 1, From the cover matrix shown below, there are multiple optimal solutions. Four patrol operators are required to cover all 30 squares. As an example, locating a patrol operator at squares 7, 9, 22, and 24 will cover all squares.
We have added grid lines, below. Student would benefit by receiving a copy of the figure. Find the farthest node from anchor node 1 node P14 and call it anchor node 2. The mid-point between the anchor nodes is the minimax location. Locate at 2, 4, and 5. Potential Sites Customer 1 2 3 4 1 1, 1, 2 2, 1, 2, 3, 3 2, 1, 1, 4 8, 6, 4, 2, 5 15, 12, 9, 6, 6 7, 6, 5, 3, 7 1, 1, 8 15, 5, 12, 2, 5 2, 4, 2, 4, 3, 2, 1, 10, Answers to Problems at the End of Chapter 10 Logging Area 1 2 3 4 Sum: Potential Sites 3 4 0 0 0 0 0 1 30 0 Locate at sites 2 and 3.
Locate at sites 1, 3, and 4. Logging Area 1 2 3 4 1 0 1, 2 Potential Sites 3 4 1, 1, 30 5 1, 90 Answers to Problems at the End of Chapter 10 Since the addition of any other site will not decrease cost, we stop. Locate only at 2 and 3. For illustration purposes, only the first iteration is shown. Iteration 1: Pairwise Exchange Savings 80 Pairwise Exchange Savings 80 Pairwise Exchange Savings 40 0 Answers to Problems at the End of Chapter 10 The largest cost reduction occurs when we exchange cells 4 and 5.
The new material handling cost is 1, This problem illustrates the issues with choosing a starting point for the algorithm. The algorithm will terminate in the second iteration without improving the solution obtained from iteration 1. For instance, starting with the following initial arrangement will result in a solution at the lower bound during the second iteration.
Iteration 1: Pairwise Exchange Savings Pairwise Exchange Savings 70 20 Pairwise Exchange Savings 60 0 0 The largest cost reduction occurs when we exchange cells 3 and 4. Iteration 1: Pairwise Exchange Savings Pairwise Exchange Savings Pairwise Exchange Savings The largest cost reduction occurs when we exchange cells 1 and 5.
The new material handling cost is 2, Iteration 1: Pairwise Exchange Savings 20 Pairwise Exchange Savings 80 60 Pairwise Exchange Savings 30 The largest cost reduction occurs when we exchange cells 3 and 5. Customize a Thing. Download All Files. Select a Collection. Save to Collection. Tip Designer. Share this thing. Send to Thingiverse user. The same identification approach has been used in the operation process chart. Additionally, fabrication op- erations have been represented with a four-digit code starting with 0.
A second viewpoint, based on graph and network theory, is to interpret the charts as network representations, or more accurately, tree representations of a pro- duction process. Company Prepared by. Air Flow Regulator Product Date. Plunger Plunger Plunger retainer Seat ring Plunger housing housing Shape, drill, Shape, Mill, Shape, Cut to tap inside drill, shape, drill, length length thread. Drill 8 Deburr holes.
Deburr and Drill 4 holes, blowout tap, ream, inspect countersink. Drill, tap, roll ream. O-ring, Lock nut A2 Pipe plug A3 Packaging A4.
The precedence diagram is a directed network and is often used in project planning. A precedence diagram for the air flow regulator is given in Figure 2. The precedence diagram shows part numbers on the arcs and denotes operations and inspections by circles and squares, respectively.
A procurement operation, , is used in Figure 2. The following convention is used in the construction of the precedence dia- gram as illustrated in Figure 2.
Purchased parts and materials that do not require modifications are placed on the top and bottom part of the diagram so that they can be inserted in the center part of the diagram when needed packaging materials, pipe plug, lock nut, spring, and O-rings.
Fabrication and assembly operations are placed in the center part of the diagram. The precedence diagram representation of the operations and inspections in- volved in a process can be of significant benefit to the facilities planner.
Packaging No additional constraints are implicitly imposed; no assumptions are made concerning which parts move to which parts; no material handling or layout decisions are implicit in the way the precedence diagram is constructed. The same claims cannot be made for the assembly chart and operation process chart. Just as there are al- ternative disassembly sequences that can be used, there are also alternative assembly sequences.
The assembly chart and the operation process chart depict a single sequence. The particular sequence used can have a major impact on space and handling system requirements. Notice operations , , , , , , and are not shown in series in Figure 2.
Hence, there exists some latitude in how the product is assembled. On the other hand, the operations process chart does not provide a mecha- nism for showing the possibility of alternative processing sequences. In order to further demonstrate our concerns regarding the misuse of the op- eration process chart in layout planning, consider the processes involved in manu- facturing an axle for an over-the-road tractor.
Using the advice typically provided in texts that describe the construction of operation process charts, the axle itself should be shown at the extreme right side of the chart. Subassemblies, components, and purchased parts would be shown sequentially feeding into the axle until a fin- ished assembly was produced.
By observing the operation process chart, one might be tempted to develop an assembly line for the axle assuming sufficient quantities are to be produced. The axle would be moved along the assembly line, and subassemblies, compo- nents, and purchased parts would be attached to it.
Using such an approach, space and handling equipment requirements for the line would be based on the largest component part in the assembly. Alternatively, and especially for low-volume production, there may be benefits to leaving the axle in a stationary position after the last operation. A large axle would require heavy duty lifting and moving equipment occupying a large space and would require high energy consumption.
Moving subassemblies and parts to the axle would need less significant material handling and space requirements, al- though there would likely be more total movements. Because of the limitations of the assembly chart and the operation process chart, we recommend a precedence diagram be constructed first. Based on the precedence diagram, alternative assembly charts and operation process charts should then be constructed. Another methodology that has made an impact on product and process design is group technology.
Group technology GT refers to grouping parts into families and then making design decisions based on family characteristics. Groupings are typically based on part shapes, part sizes, material types, and processing requirements.
In cases where there are thousands of individual parts, the number of families might be less than Group technology is an aggregation process that has been found to be use- ful in achieving standardized part numbers and standard specifications of purchased parts, for example, fasteners and standardized process selection [6, 9, 11, 12, 16 ].
The importance of the process design or process plan in developing the facil- ities plan cannot be overemphasized. Furthermore, it is necessary that the process planner understand the impact of process design decisions on the facilities plan. Our experience indicates that process planning decisions are frequently made with- out such an understanding.
As an example, it is often the case that alternatives exist in both the selection of the processes to be used and their sequence of usage. The final choice should be based on interaction between schedule design and facilities planning. The resulting standardization of process selection has yielded considerable labor savings and reductions in produc- tion lead times. At the same time, standardization in process selection might create disadvantages for schedule and facility design.
If such a situation occurs, a mecha- nism should exist to allow exceptions. Many of the degrees of freedom available to the facilities planner can be affected by process selection decisions.
Production quantity decisions are referred to as lot size decisions; determining when to produce is referred to as production scheduling. In addition to how much and when to produce, it is important to know how long pro- duction will continue. Such a determination is obtained from market forecasts. Schedule design decisions impact machine selection, number of machines, number of shifts, number of employees, space requirements, storage equipment, material handling equipment, personnel requirements, storage policies, unit load design, building size, and so on.
Consequently, schedule planners need to interface continuously with marketing and sales personnel and with the largest customers to provide the best information possible to facilities design planners. To plan a facility, information is needed concerning production volumes, trends, and the predictability of future demands for the products to be produced.
The less specificity provided regarding product, process, and schedule designs, the more general purpose will be the facility plan. The more specific the inputs from product, process, and schedule designs, the greater the likelihood of optimizing the facility and meeting the needs of manufacturing.
Lastly, consider a facility that pro- duces 10, television sets per month for the next 10 years versus one that produces 10, television sets per month for three months and is unable to predict what product or volume will be produced thereafter; they too should differ. As a minimum, the market information given in Table 2.
Prefer- ably, information regarding the dynamic value of demands to be placed on the fa- cility is desired. Ideally, information of the type shown in Table 2. Packaging 2. Susceptibility to product changes 3. Susceptibility to changes in marketing strategies Where are the consumers located?
Facilities location 2. Method of shipping 3. Warehousing systems design Why will the consumer purchase the product? Seasonability 2.
Variability in sales 3. Packaging Where will the consumer purchase the product? Unit load sizes 2. Order processing 3. Packaging What percentage of the market does the product 1. Future trends attract and who is the competition 2. Growth potential 3. Need for flexibility What is the trend in product changes? Space allocations 2. Materials handling methods 3. Need for flexibility. If such information is available, a facilities plan can be developed for each demand state, and a facility designed with sufficient flexibility to meet the yearly fluctuations in product mix.
By developing facilities plans annually and not- ing the alterations to the plan, a facilities master plan can be established. Dynamic layouts can be designed to accommodate varying product demands [14]. In many cases, however, information of the type given in Table 2. Therefore, facilities typically are planned using deterministic data.
The assumptions of deterministic data and known demands must be dealt with when evaluating alter- native facilities plans. In addition to the volume, trend, and predictability of future demands for var- ious products, the qualitative information listed in Table 2.
Ad- ditionally, the facilities planner should solicit input from marketing as to why market trends are occurring. Such information may provide valuable insight to the facilities planner.
Surprisingly, his observations apply to several aspects of facilities planning. Such a situation is depicted by the volume-variety chart, or Pareto chart, given in Figure 2. By knowing this at the outset, development of the facilities plan may be significantly simplified. This volume-variety information is very important in determining the layout type to use.
Schedule design determines the number of each equipment type required to meet the production schedule. Specification of process requirements typically occurs in three phases. The first phase determines the quantity of components that must be produced, including allowances for defective items, in order to meet the market estimate. The second phase determines the machine requirements for each operation, and the third phase combines the operation requirements to obtain overall machine requirements.
We define an item to be defective when the final attributes after processing do not meet the control limits specified by quality control standards. A review of Figure 2.
The concept is general in the sense that the component used in an as- sembly may be a purchased component, and the defective percentage gives the estimate of the percent of rejects from an arriving lot. It is always better to achieve zero defects for many reasons, including the elimination of wasteful activities related to handling defective items. Some parts might be scrapped while others may be reworked. Fewer defects usually result from more automated processing, looser part tolerance, the use of certified suppliers, quality at the source, prevention techniques, and use of higher-grade materials.
All of these factors point to fundamental economic trade-offs. The required inputs to manufacturing and assembly operations can be deter- mined as follows. Let dk represent the percentage of defective items produced on the kth operation, Ok the desired output without defects, and Ik the production in- put.
Example 2. The market estimate is the output required from step 3. As a general principle, it is desirable to design processes with zero defects. Should this not be possible, there should be fewer defects at processes that are near the end of the manufacturing steps. The reason is that the cost of the item increases as more operations are performed on it. The graphical representation for operations with rework is shown in Figure 2. Given that rework is performed based on the assumption above, calculate the number of units required for processing at the first op- eration.
We assume that the components are outsourced and the final assembly is performed locally. The final products are two assemblies requiring three components. As- sembly 1 requires four units of component 1 and three units of component 2. Assembly 2 requires two units of component 2 and one unit of component 3.
See Figure 2. The calculations required are also shown in Figure 2. The calculations performed using Equations 2. However, when pro- ducing small batches, the use of average values is less appropriate. If conditions are such that the foundry has only one chance to produce the number of castings required, then the probability of a casting being good should be considered when determining the batch size to be produced.
In determining how many castings to produce, the following questions come to mind: 1. How much does it cost to produce a good casting? How much for a bad casting? How much revenue is generated from a good casting? How much from a bad casting?
What is the probability distribution for the number of good castings resulting from a production lot? If answers are available for these questions, then a determination can be made re- garding the number of castings to schedule in order to, say, maximize the expected profit or achieve a desired confidence level of not producing fewer good castings than are needed.
Determining the number of additional units to allow when sched- uling low-volume production where rejects randomly occur is called the reject al- lowance problem [17]. If it is desired to maximize expected profit, the value of Q that maximizes Equation 2.
For most cost and revenue formulations, Equation 2. The necessary and sufficient conditions for the optimal production quantity Q when X is binomially distributed is given in [17].
An order for 20 custom-designed castings has been received. Based on historical records, the probability dis- tributions given in Table 2. How many castings should be scheduled.
What is the probability of losing money at this production level? The profits resulting from various combinations of Q and x are shown in Table 2. The vector prod- ucts of columns from Tables 2. From Table 2. We use the term machine fractions. The machine fraction for an operation is determined by dividing the total time re- quired to perform the operation by the time available to complete the operation.
The total time required to perform an operation is the product of the standard time for the operation and the number of times the operation is to be performed. For ex- ample, if it takes 0. Whether or not 1. Are the parts actually being made to the 0. Is the machine available when needed during the two-hour period? Are the standard time, the number of parts, and the time the machine takes known with certainty and fixed over time?
The first question may be handled by dividing the standard time by the histor- ical efficiency of performing the operation. The reliability factor is the percentage of time the machine is actually producing.
The third question dealing with the uncertainty and time-varying nature of machine fraction variables can be an important factor in determining machine re- quirements. If considerable uncertainty and variation exist over time, it may be useful to consider using probability distributions instead of point estimates for the parameters and utilizing a stochastic machine fraction model. Typically, such mod- els are not utilized, and the approach taken is to use a deterministic model and plan the facility to provide sufficient flexibility to handle changes in machine frac- tion variables.
In Equation 2. During an eight-hour shift, units are to be produced. How many milling machines are required? Such a determination is not necessarily straight- forward. Even if only one operation is to be performed on a particular equipment type, overtime and subcontracting must be considered.
If more than one operation is to be run on a particular equipment type, several alternatives must be considered. No drill press operator, overtime, or subcontracting is available for any operation on the ABC drill press.
It may be seen that a minimum of four and a maximum of six machines are required. How many should be purchased? The answer is either four, five, or six. With no further information, a specific recommendation cannot be made. Clustering considerations may require the application of group technology methods to determine the commonality of parts and make decisions of how the ma- chines are assigned to departments.
A job shop type of layout will result in fewer machines, while dedicated production lines will require values that are closer to the upper bounds as listed in the last column in Table 2. Clustering analysis is covered in Chapter 3, and determination of layout configurations is discussed in Chapter 6. It is assumed that a deter- mination of the number of people to be employed in the facility already has been made. Typically, such decisions are not a part of the facilities planning process.
However, the combination of product, process, and schedule design decisions sig- nificantly influences the number of employees involved in producing the product. In this section, we consider how decisions regarding the assignment of machines to operators can affect the number of employees.
Specifically, we consider a situation involving the assignment of operators to semiautomatic production equipment. For purposes of this discussion, it is assumed the machines are identical. In contrast to the reject allowance problem, it is assumed that the times required to load and un- load each machine are constant, the automatic machining time is constant, and the time required for the operator to travel between machines, prepare parts for ma- chining, and inspect and pack parts is constant.
To illustrate the situation under consideration, see Figure 2. The chart is called a human- machine chart or a multiple activity chart, since it shows the activities of one or more people and one or more machines. Such charts can be used to analyze multi- ple activity relationships when nonidentical machines are being tended by one or more operators.
As shown, the analysis begins with each machine empty and the operator standing in front of Machine 1 M The oper- ator loads M-1, walks to M-2, loads M-2, walks to M-3, loads M-3, walks to M-1, unloads M-1, loads M-1, inspects and packs the part removed from M-1, travels to M-2, and so forth. As shown in Figure 2. In other words, if nothing interrupts the activities of the operator and the three machines, the 9-minute cycle will repeat indefinitely.
Under conditions similar to those depicted by Figure 2. T-3 3 L-3 Loaded 4 Machining. Transient State 12 min T Hence, an ideal assignment is. Since a fractional number of machines cannot be assigned to an operator, consider what will happen if some integer number of machines, m, is assigned. The repeating cycle will be the larger of the two, and the difference in the two will be idle time. If we wish to determine the cost per unit produced by an m machine assignment, the following notation will be helpful:.
Finished product Raw material Figure 2. Reprinted with permission from [18]. Assuming each machine produces one unit during a repeating cycle, the cost per unit pro- duced during a repeating cycle can be determined as follows:. Hence, from Equation 2. Therefore, H equals 0. The problems at the end of the chapter explore various aspects of the machine assignment problem, such as assigning machines to operators if, say, a total of 11 machines are required to meet the daily production schedule or there is uncertainty re- garding the value of Cm.
Some typical business objectives include breakthroughs in production cost, on-time deliv- ery, quality, and lead time. Some tools frequently used by quality practitioners e. The seven management and planning tools have gained acceptance as a methodology for improving planning and implementa- tion efforts [5].
In the mids a committee of engineers and scientists in Japan refined and tested the tools as an aid for process improvement, as proposed by the Deming cycle. In , Dr. Deming proposed a model for continuous process improvement that involves four steps: planning and goal setting, doing or execution, checking or analysis, and performing corrective actions Plan—Do—Check—Act. The seven management and planning tools are the affinity diagram, the inter- relationship digraph, the tree diagram, the matrix diagram, the contingency diagram, the activity network diagram, and the prioritization matrix.
Each is described below and illustrated with examples related to facilities design. Suppose we are interested in generating ideas for reducing manufacturing lead time.
Each group then receives a heading. An affinity diagram for reducing manufacturing lead time is presented in Figure 2. The headings selected were facilities design, equipment issues, quality, setup time, and scheduling.
The term digraph is employed because the graph uses directed arcs. Suppose we want to study the relationship. Issues in reducing manufacturing lead time. Facilities design Equipment issues Quality Setup time Scheduling. Form 1. Operator cer- 1. Provide 1. Provide doc- 1. Provide visi- product fam- tification training on umentation bility to daily ilies program how to use on setup product se- process doc- procedures quence 2.
Assign fami- 2. Sit techni- umentation lies to cells cians closer 2. Locate fix- 2. Do not au- to produc- 2. Implement tures and thorize prod- 3. Monitor with feed- needed parts breakdowns back 3. Provide are not avail- 4. Keep receiv- to predict fu- training so ing and ship- able ture oc- 3. Develop operators ping close to curences mistake- can partici- 3. Negotiate production proof pate frequent and 4.
Recruit devices smaller lots enough tech- 4. Provide in- to customers nicians per 4. Develop ca- formation on shift pabilities for daily se- monitoring quence key machine parameters Figure 2. Form product 2. Assign families 3. Assign raw materials families to manufacturing to their point of cells use. Keep receiving and shipping close to production.
The interrelationships are presented in Figure 2. Note that this graph helps us understand the logical se- quence of steps for the facilities design. The efforts must be initiated with the forma- tion of product families. Assuming that we want to con- struct a tree diagram for the formation of product families, the tree is presented in Figure 2. Note that the same exercise can be performed for each item in the in- terrelationship digraph.
Determine part usage per product. Compound Identify unique parts per product similarities. Identify common products. Determine machines needed per product. Machines used Identify machine sequence per product. Product family Identify bottleneck machines formation. Review product forecasts Demand per product Conduct P-Q analysis.
Determine precision requirements by product Machine capabilities Determine machine capabilities. A simple application of this tool is the de- sign of a table in which the participants and their role within the small teams are de- fined.
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