Intermediate Systems Acquisitions Course. The Manufacturing Process

Transcription

1 The Manufacturing Process Historically, for hardware-intensive programs, production and deployment costs account for about one third of the total life cycle cost of a system. These ratios will vary for software-intensive programs. Ensuring efficient manufacturing processes and closely monitoring these processes is essential to controlling costs and maintaining delivery schedules. In a previous lesson we discussed the first two steps required to integrate production concerns into the systems acquisition process: (1) influence the design process and (2) prepare for production. In this lesson, we will address the third step: execute manufacturing. You will learn about some key elements of a successful manufacturing process, such as: Lean manufacturing Process proofing Statistical process control - a tool for variability analysis and reduction The learning curve You may print The Manufacturing Process lesson or save it for future reference. Page 1 of 27

2 Objectives Upon completion of this lesson, you should be able to: Recognize the principles of lean manufacturing Describe methods for achieving quality products Describe learning curve theory Given a product structure, identify the optimal process structure for the manufacturer of a product Page 2 of 27

3 Lean Manufacturing Lean manufacturing was developed by Toyota in Japan, between the 1940s and 1990s, as a way to compete with American car manufacturers. It is based on the philosophy of continuous process improvement, which may be applied to a traditional hardware assembly line, or a software production effort using agile principles. There are two main principles of lean manufacturing: Minimization of waste Responsiveness to change These two principles complement and support each other. Taken together, these principles drive the lean manufacturing processes to be flexible and changeable while minimizing waste. Also, they enable production decision authority at the lowest possible level in the organization. Lean manufacturing processes are agile, and agile processes, by nature, are also lean. When implementing a lean manufacturing process it is important to focus equally on both the underlying lean philosophy and certain lean tools and techniques that are used in implementing that philosophy. Lean processes cannot be implemented simply through the use of lean tools in isolation from the underlying management vision and approach. D Page 3 of 27 Lean manufacturing, which is often known simply as lean, is a production practice that considers the expenditure of resources for any goal other than the creation of value for the end customer to be wasteful, and thus a target for elimination. A graphic shows that the two main principles of lean manufacturing, (1) respond to change, and (2) minimize waste, complement and support each other.

4 Lean Manufacturing: Minimization of Waste The first principle of lean manufacturing is minimization of waste. In lean manufacturing, waste is the use of resources, or the performance of activities, that are not necessary to create the desired value in a project. Waste can result from a number of factors, for example: Inefficient layouts may result in extra time or personnel to complete a task Defective equipment may lead to assembly line downtime due to repairs Unnecessary paperwork may require extra time and personnel Excess inventory may result in storage costs, money tied up in inventory, unused inventory, or inventory spoilage Typical factory layouts, for example, have assembly lines with workers side-by-side, each operating one machine on the line. If any worker needs a different tool, they must stop the line until they find the tool. A lean alternative is a u-shaped cell with one employee in the center responsible for the production cell. Each employee would know how to work multiple machines, each cell would have its own set of tools, and each tool would have a map to its location. This arrangement could result in an average increased efficiency of 15 percent. Page 4 of 27

5 Lean Manufacturing: Responsiveness to Change The second principle of lean manufacturing is responsiveness to change. The key to being responsive to change is to reduce reaction time to such things as: New customer or design requirements New technology Market demand For example, during production, the customer/user requests a change to the new U.S. Coast Guard (USCG) patrol boat's wheelhouse arrangement. Before the advent of lean manufacturing, this would have caused delays in the production process while design and production engineers modified drawings and manufacturing processes. During this redesign process, production and assembly teams would historically stand idle. With lean manufacturing, workers are trained in a number of different skills, so they are able to work on alternate areas (for example, machinery control systems) while the wheelhouse arrangement is redesigned. The result is that customer requirements are met and impacts to the production timeline are minimized because idle time was essentially avoided. Page 5 of 27

6 Overarching Requirements For lean manufacturing to be successful, there are two overarching requirements: Everyone must participate in continuous process improvement and other lean manufacturing practices, from the workers on the factory floor to top management Teams must be empowered to make decisions that, previously, only management could make When these two requirements are followed, workers are able to change their processes quickly and efficiently, resulting in significant productivity gains. Page 6 of 27

7 Knowledge Review Which of the following describes a lean manufacturing practice? A. An ideal floor layout is established before manufacturing begins and is not altered B. All significant decisions are made by senior management C. Teams are instructed to keep exhaustive records of all manufacturing processes D. Late in the manufacturing process, the team inserts new sensor technology requested by the customer into the product with minimal impact on schedule. Correct! Lean manufacturing operations are able to reduce reaction time to respond to new customer requirements and new technology. Page 7 of 27

8 Producing Quality Products Whether a production organization has implemented lean processes or not, all production organizations have to be concerned with producing high quality products while still controlling manufacturing costs. There are three basic categories in which a manufacturer may spend funds to achieve and maintain production quality: prevention, appraisal, and failure correction. Prevention - avoiding problems in the first place by means such as process proofing and variability reduction Appraisal looking for errors through testing and inspection Failure Correction fixing errors, often through rework or repair It is best to minimize failure correction costs through prevention. The cost of preventing mistakes is generally less than the cost of correcting them after they are found. One of the most important factors for preventing problems, and thereby creating high-quality products and controlling costs, is production stability. Production stability is achieved through: Process proofing Measuring and reducing variability, using tools such as statistical process control (SPC) Page 8 of 27

9 Process Proofing Process proofing is the act of verifying that the production process is optimized before the start of production. Personnel would examine areas such as: Tool design Assembly methods Personnel training You can use process proofing to eliminate early production problems. Example: When manufacturing the new highly skewed propeller for the USCG drug interdiction speed boat, manufacturing engineers must verify that the tool will deliver the needed accuracy before investing in a complex computer-controlled machining tool. The production process must be tested on a smaller scale to ensure that it will deliver the stated accuracy. The testing of small scale production runs is usually part of the low rate initial production (LRIP) run. Production testing may also be done during prototype development as part of the overall product development effort. The goal is to identify production problems early, to ensure solutions can be found prior to full-rate or full-scale production. Page 9 of 27

10 Statistical Process Control A manufacturer may produce thousands of units of the same item using a highly standardized process, but there will always be some degree of variability in the final products, such as slight variations in their physical dimensions. One of the most important things to ensure production stability is to measure and reduce this variability. Products with less variability can help reduce the production costs of a system. One common tool for measuring variability is the statistical process control (SPC) chart. An SPC chart helps the manufacturer determine whether its production process has a stable, predictable degree of variability. An SPC chart shows when variations are at an unacceptably high level. It can also be used to anticipate when variations are trending toward an unacceptably high level, allowing the manufacturer to correct problems in the manufacturing process before the variations become too great. Page 10 of 27

11 Statistical Process Control (continued) An SPC chart displays variations in the measurements of products. The key features of an SPC chart include: Upper control limit: marks the upper end of the acceptable range Lower control limit: marks the lower end of the acceptable range A median central reference line between the control limits A process is said to be in a state of statistical control when the process measurements are within the upper and lower control limits, and their variations are random. An in-control process will have a stable, predictable degree of variability. The SPC chart below displays an in-control process. A process is out of control when one of the measures exceeds the upper or lower control limit, or the variations display some other nonrandom pattern. The manufacturer can often use non-random patterns on an SPC chart to detect an out-ofcontrol process before the upper or lower control limits are actually breached, allowing it to intervene and prevent production waste due to products that break specification requirements. D Select the D-link to read a detailed explanation of the graphic Page 11 of 27 An example of a non-random pattern would be seven consecutive points above the reference line, or seven consecutive points below the reference line. Even if these measurements are within the control limits, the process is statistically out of control, meaning the variations are no longer stable and predictable, and could be trending toward a breach of a control limit. An X-Y graph showing a statistical process control chart. The Y-axis shows measurements ranging from -4.0 to 4.0, and the X-axis shows observations from 0 to 20. There are three horizontal lines: the upper control limit at about 2.8, the lower control limit at about -3.2, and the median reference line at about Eighteen observations are plotted as points from left to right. A line connects the points, curving up and down, above and below the reference line, but staying within the upper and lower control limits.

12 SPC Chart Example In this example, a manufacturer produces hundreds of one-meter steel trusses each week. The SPC chart below shows the actual length of one sample truss produced each day over 12 days. What does the chart show about the process? Is it in statistical control? Is it out of control? Select the image to view an enlargement. Select the D-link to read a detailed explanation of the graphic Note the specification limits for the trusses are 1003 mm and 997 mm. All 12 sample trusses are within the specifications, or "in spec." However, in this chart, the upper control limit is mm, while the lower control limit is mm. On day 7, the length of the sample truss exceeded the upper control limit; therefore the process is out of control. Note that the measurement also dropped below the lower control limit on day 11. D Page 12 of 27 A statistical process control chart with the length of the trusses, in millimeters, plotted from day 1 to day 12. The reference line is at mm. The upper control limit is mm and the lower control limit is mm. The 12 sample measurements as follows: 999.2, , 998.8, , , 999.9, , 999.2, , , 997.1, A line connects each of the plotted points, alternating above and below the reference line. The day 7 measurement of mm exceeds the upper control limit, and the day 11 measurement of mm falls below the lower control limit. There is also an upper specification limit at mm and a lower specification limit at 997 mm. All 12 measurements are within the specification limits.

13 Common Cause and Special Cause Variations Variations may result from common causes or special causes. Select each button to learn more: As previously noted, a process is out of control when measurements exceed the upper or lower control limit, stay above or below the reference line for seven consecutive measurements, or display other non-random patterns. These non-random patterns are the result of special causes. The variations in controlled processes, on the other hand, are due to common cause variability. Page 13 of 27 Common causes are the inherent characteristics of the process, such as the machine design, floor layout, or personnel training. Common cause variations are random because they are not due to any specific problems with the manufacturing process, but rather the natural, random variability that is inherent to any physical system. This natural, random variability has predictable limits, therefore, common cause variability is predictable and stable. If the manufacturer wishes to reduce common cause variability, it must improve the overall process. Improvements would typically include better machines, more training, or more management involvement. Special causes are unique issues, such as broken equipment, changes in environmental conditions like moisture or temperature, or a missing team member. Special cause variations are non-random because there is a specific influence pushing the measurements in a particular direction, rather than just the normal, random variability of physical systems. Because special cause variability is triggered by a unique event, it is difficult to predict such events based on the past history of the particular process. Special cause variations are corrected on a case-by-case basis, often through specific interventions by the workers.

14 Why Control Limits Matter The purpose of the SPC chart is to minimize production waste. The chart helps the manufacturer prevent or resolve problems in the manufacturing processes that could result in products that break the specification limits and are therefore waste. Control limits are different than, but related to, specification limits. Specification limits are the actual customer requirements for the finished product. Control limits are established using statistical analysis. If the process is in control, it is statistically very unlikely to produce items that are outside the control limits. Assuming the specification limits are set outside the control limits, an in-control process will almost certainly produce in-spec products. In the example of the trusses, the customer requires the one-meter trusses to be between 1003 mm and 997 mm. The control limits are within the specification limits. If the process were in control, it would be very unlikely that the process would result in out-of-spec trusses, from a statistical perspective. The process in this example is out of control, however. There is, therefore, a heightened risk that the process will result in out-of-spec products in the future, despite the fact that all 12 of the sampled products were in-spec. The SPC chart allows the manufacturer to detect when a problem is affecting a process, therefore allowing manufacturers to resolve the problem before products are produced outside of customer specifications. Page 14 of 27

15 SPC Benefits Below are some of the benefits of using the SPC method: Focuses attention on detecting and monitoring process variation over time Serves as a tool for ongoing process control Helps a process to perform consistently, more predictably, with higher quality, lower cost, and higher effective capacity Provides a common language for discussing process performance Page 15 of 27

16 Knowledge Review An SPC chart for a milling process indicates that the upper control limit has been exceeded. What information does the SPC chart provide that would be useful to a decision maker? A. Estimate of program completion B. Manufacturing process is on schedule C. Process is out of control D. Design meets user expectation Correct! The decision maker will recognize that the process is out of control and take the appropriate remedial action. Page 16 of 27

17 Learning Curve Theory Production costs may also decrease as workers become more experienced. Production costs tend to go down as the cumulative quantity produced goes up. This phenomenon is known as the learning curve. Learning curve theory assumes that each time the cumulative number of items produced doubles, the hours needed to produce each item decrease by a fixed percentage. The more items are produced, the less it should cost per item, as workers become more experienced and efficient. By applying learning curve theory, we can better estimate the cost of producing various quantities of an item. This information can be useful in planning the program as well as during actual production. Page 17 of 27

18 Learning Curve Conditions Learning curve theory does not apply in all production situations. The theory is most applicable in situations where the following conditions exist: Uninterrupted serial production The manufacturing process is continuous without breaks for material, manufacturing changes, financial challenges, or requirement changes Consistent product design The design is stable, permitting workers to gain more and more experience in assembly of individual items Management emphasis on productivity improvement Upper and mid-level managers must show interest and support for improvements Software-intensive programs do not directly apply learning curve theory when procuring equipment, because learning curve theory does not apply readily to the writing of software code. However, the manufacturers of the hardware used in these programs may use the learning curve. Page 18 of 27

19 Factors Influencing the Learning Curve When the learning curve is steeper, increased production quantities result in greater time savings. When the learning curve is flatter, increased production quantities still result in time savings, but the savings are smaller. A variety of factors influence whether the learning curve applies to a particular process, as well as how flat or steep the learning curve is: Item complexity The simpler the process, the flatter the learning curve will be. The more complex an item is, the steeper the learning curve will be. This is because there are more opportunities for workers to learn and to improve the production process. Manufacturing methods and processes The more automation involved in a production process, the flatter the learning curve will be. The less automated the process, the steeper the learning curve will be. Workforce stability The higher the turnover rate of the workforce, the flatter the learning curve will be Production breaks If there is a break in the production timeline, there may be a lack of experienced veterans to train new workers on the job, resulting in a flatter learning curve, at least initially For more background on learning curves, see the publications of H. Paul Barringer, P.E. Page 19 of 27 H. Paul Barringer, P.E., Barringer & Associates, Inc., "Predict Future Failures From Your Maintenance Records," 2003

20 Learning Curve - Example In the example below, the labor cost of producing the first 20 units is shown on the chart. The cost per unit decreases over time. In this example, which shows an 80 percent learning curve, every time the cumulative number of units produced doubles, the cost per unit decreases by 20 percent. For example, the cost to produce unit 1 is $100, the cost of unit 2 is $80, and the cost of unit 4 is $64. Select the D-link to read a detailed explanation of the graphic D Page 20 of 27 An X-Y graph displays an 80% learning curve. The Y axis is cost per unit and the X axis is the unit number. The cost per unit decreases as the number of units produced increases. Unit 1 costs $100, unit 2 costs $80, unit 4 costs $64, unit 8 costs $51.20, and unit 16 costs $ A smoothly declining curve connects these points and continues until unit 20, gradually becoming more level but continuing to decline.

21 Learning Curve Slope Below is a flatter 95% learning curve. Each time the production quantity doubles, the cost per unit decreases by only 5%. D Select the D-link to read a detailed explanation of the graphic Page 21 of 27 An X-Y graph displays a 95% learning curve, which is significantly less steep than the 80% learning curve. The Y axis is cost per unit and the X axis is the unit number. The cost per unit decreases as the number of units produced increases. Unit 1 costs $100, unit 2 costs $95, unit 4 costs $90, unit 8 costs $85.74, and unit 16 costs $ A smoothly declining curve connects these points and continues until unit 20, gradually becoming more level but continuing to decline.

22 Knowledge Review In which of the following situations would you expect to apply a steep learning curve to production labor costs? A. There is a high turnover of factory personnel B. The design of the product is complex C. The production process is highly automated D. There are likely to be frequent breaks of the production process Correct! The more complex an item is, the steeper the learning curve will be. This is because there are more opportunities for workers to learn and to improve the production process. Page 22 of 27

23 Product Structures and Process Structures Manufacturing operations may range from mass-production operations to producers of one-of-akind items. Manufacturers that produce highly standardized items can generally produce them at a higher volume, while manufacturers that produce a greater diversity of items will generally produce each item at a lower volume. The manufacturer's balance between the volume and diversity of its products is known as its product structure. For every product structure, there is an optimal process structure, which is the physical layout of the production operation. The four product and process structures are shown on the graphic. These categories are theoretical. In practice, a manufacturing operation may fall somewhere on a continuum between these four. D Select the image to view an enlargement Select the D-link to read a detailed explanation of the graphic Page 23 of 27 A chart showing a continuum of four product structures, with the optimal process structure and examples for each product structure displayed below. First are operations that produce a standardized product at a very high volume. The optimal process structure for these operations would be a continuous flow. An example of an operation with this product and process structure would be a fuel refinery. Second are operations that offers fewer product lines, but at a high volume. Their optimal process structure would be a connected line flow. An example is a radio assembly plant. Third are operations that are capable of offering diverse product lines, but at a low volume. Their optimal process structure would be a disconnected line flow. An example is a boat hoist manufacturer. Last are operations that make one-of-a-kind products at a very low volume. Their optimal process structure would be jumbled flow. An example is an experimental robotics laboratory.

24 Product Structures and Process Structures: Examples On one end of the continuum would be a fuel refinery, which produces a highly-standardized, highvolume commodity. The fuel would be produced under a continuous flow process structure. In continuous flow, the product or commodity is interchangeable and standard, and is produced at a high volume. A continuous flow process has a fixed structure that cannot change without changing what is being produced. Altering the production process for marine fuel, for example, would result in something other than marine fuel. on the continuum would be a radio assembly plant that produces several different radio models, but can still produce them all at a relatively high volume. The plant is likely to use a connected line flow process, where items are mass-produced with an assembly line. Items are passed through a series of stations, each performing a task and using interchangeable parts. A connected line flow process has a fixed structure, but it can be changed. For example, the radio assembly plant might re-tool some of its assembly lines to add hardened cases or change from an external to an internal antenna. Despite these changes, the plant is still making radios. From the program management perspective, low rate initial production (LRIP) and full rate production are most applicable when dealing with continuous line flow and connected line flow. D Page 24 of 27 Reprise of product and process structure chart, but showing only the first two categories: continuous flow, connected line flow, and their associated product structures and examples.

25 Product Structures and Process Structures: Examples (continued) would be manufacturers of heavy equipment, such as boat hoists to transport USCG vessels. A boat hoist manufacturer will likely use the same facility to produce a variety of specialized models to meet diverse customer needs, and will produce each model at relatively low volumes. Such operations are likely to use a disconnected line flow process. In disconnected line flow, batches of a particular model proceed irregularly through several different work stations, although each work station may use a standardized process. The manufacturer might produce just a few basic machines but be able to add dozens of combinations of optional modifications. A disconnected line flow process does not have a fixed structure; each batch of products could go through a different sequence of stations without having to re-tool the plant. Finally, a laboratory that produces prototype HAZMAT robots for the Science and Technology (S&T) Directorate would produce the greatest diversity of items at the lowest volume, because all of its products are one-of-a-kind. The laboratory is most likely to use a jumbled flow process, which employs specialized material and unique, flexible assembly methods. Disconnected line flow and jumbled flow involve more individual tailoring and customization for the customer, so the program management office should plan on more active engagement and oversight when dealing with these processes. In special cases, manufacturers may choose a process structure that is atypical for their product structure. For more discussion, see the classic 1979 Harvard Business Review article on this topic. D Page 25 of 27 Robert H. Hayes, and Steven C. Wheelwright. (1979). Link Manufacturing Process and Product Life Cycles. Harvard Business Review. Available at: Reprise of product and process structure chart, but showing only the last two categories: disconnected line flow, jumbled flow, and their associated product structures and examples.

26 Knowledge Review Customs and Border Protection (CBP) requires 30 large, diesel-powered 4x4 vehicles with several upgrades, including heavy-duty batteries, front bumper winches, and hardening for extreme desert conditions. The optimal manufacturer for this job would be set up for which process structure? A. Jumbled flow B. Disconnected line flow C. Connected line flow D. Continuous flow Correct! The optimal manufacturer would be able to efficiently produce standard 4x4 units but also have the capacity to build in a variety of optional upgrades in irregular, or disconnected order. Page 26 of 27

27 Summary In this lesson you learned the two main principles of lean manufacturing: minimization of waste and responsiveness to change. Programs that incorporate lean manufacturing principles and techniques tend to save money and time (minimization of waste) while remaining flexible enough to meet ever-changing customer demands (responsiveness to change). You also learned about three categories of costs for achieving quality: prevention, appraisal, and failure correction. It is generally less expensive to prevent problems than to correct them. Process proofing and statistical process control (SPC) are key tools for preventing problems. Process proofing is the act of verifying that processes are optimized before production begins. SPC is a powerful tool for process monitoring and detection of variations. SPC is used to help a process perform more predictably, leading to higher quality and lower cost. Costs may also be reduced as workers become more experienced. Learning curve theory assumes that each time the cumulative number of items produced doubles, the hours needed to produce that item decrease by a fixed percentage. Finally, you learned about four product structures for manufacturing operations, and the process structure that is optimal for each one. For operations that produce standardized products at a very high volume, continuous flow is optimal. Operations that produce a few product lines at a relatively high volume likely use a connected line flow. Operations that produce diverse product lines at a relatively low volume are likely to use a disconnected line flow. Operations that produce one-of-akind products would most likely use a jumbled flow process. You may print The Manufacturing Process lesson or save it for future reference. Page 27 of 27