...Reducing the lead time of litho printing sample making process at Avery Dennison Lanka INTRODUCTION Avery Dennison Lanka (Pvt) Ltd is a company, which is situated in Biyagama free trade zone. Avery Dennison is a multinational company which is spread among 60 countries over the world. The company ranked number 362 on the 2010 fortune 500 list of the largest U.S. industrial and service companies. The CEO is Dean A. Scarborough. There are around 600 employees working in the company. Avery Dennison develops, manufactures and sells products through four groups of businesses as Pressure‐sensitive Materials, Retail Information Services, Office and Consumer Products and other specialty converting businesses. This Company's products include pressure‐sensitive labelling materials, graphics imaging media, retail apparel ticketing and branding systems, RFID inlays and tags, office products, specialty tapes, and a variety of specialized labels for automotive, industrial and durable goods applications. In Sri Lanka, products are narrowed down to labels and tags which give information about a specific garment good. Garment manufacturers can be considered as the main customers of Avery Dennison Lanka (Pvt) Ltd. Thus such tags are to be manufactured in large quantities. In order to get a satisfactory product that meets the customer need, first the samples has to be fabricated. The sample making process can be identified as the bottle‐neck of the whole litho‐printing process...
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...CHAPTER IV STATISTICAL PROCESS CONTROL * This chapter covers two topics that are increasingly important in business organizations: quality control and continuous improvement. * Quality control focuses on the conversion of inputs into outputs. * The purpose of quality control is to assure that processes are performing in an acceptable manner. * This is accomplished by monitoring process output using statistical techniques. * If the results are acceptable, no further action is required; unacceptable results call for corrective action. * In the best companies, the emphasis is on designing quality into the process, thereby greatly reducing the need for inspection or control efforts. -As you might expect, different business organizations are in different stages of this revolutionary process: * The least progressive rely heavily on inspection. * Many occupy a middle ground that involves some inspection and a great deal of process control. And the most progressive have achieved an inherent level of quality that is high enough that they are able to avoid wholesale inspection activities as well as process control activities. That is the ultimate goal. Figure 4-1 illustrates these phases of quality assurance. Figure 4-1 Phases of quality assurance Acceptance Sampling Inspection before/after production Corrective action during production Quality built into the process process Acceptance Sampling ...
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...Chapter 6 Statistical Process Control 6.0 Introduction One of the axioms or truisms in law of nature is “No two items of any category at any instant in the universe are the same”. Manufacturing process is no exception to it. It means that variability is part of life and is an inherent property of any process. Measuring, monitoring and managing are rather engineers’ primary job in the global competition. A typical manufacturing scenario can be viewed as shown in the Figure 6.1. That is if one measures the quality characteristic of the output, he will come to know that no two measured characteristics assume same value. This way the variablility conforms one of the axioms or truisms of law of nature; no two items in the universe under any category at any instant will be exactly the same. In maunufacturing scenario, this variability is due to the factors (Random variables) acting upon the input during the process of adding value. Thus the process which is nothing but value adding activity is bound ot experience variability as it is inherent and integral part of the process. Quality had been defined in many ways. Quality is fitness for use is the most common way of looking at it. This fitness for use is governed by the variability. In a maufacturing scenario, despite the fact that a machine operator uses the same precision methods and machines and endeavours to produce identical parts, but the finished products will show a definite variablity. The variability of a product...
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...Plastic key chains are being produced in a company named Hot Shot Plastics. The plastic material is first molded and then trimmed to the required shape. The current curetimes (which is the time for plastic to cool) during the molding process affect the edge quality of the key-chains produced. The aim is to achieve statistical control of the curetimes using Xbar and R-charts Curetime data of 25 samples, each of size 4 have been taken when the process is assumed to be in control. These are shown below. Sample no | Observations | 1 | 27.34667 | 27.50085 | 29.94412 | 28.21249 | 2 | 27.79695 | 26.15006 | 31.21295 | 31.33272 | 3 | 33.53255 | 29.32971 | 29.70460 | 31.05300 | 4 | 37.98409 | 32.26942 | 31.91741 | 29.44279 | 5 | 33.82722 | 30.32543 | 28.38117 | 33.70124 | 6 | 29.68356 | 29.56677 | 27.23077 | 34.00417 | 7 | 32.62640 | 26.32030 | 32.07892 | 36.17198 | 8 | 30.29575 | 30.52868 | 24.43315 | 26.85241 | 9 | 28.43856 | 30.48251 | 32.43083 | 30.76162 | 10 | 28.27790 | 33.94916 | 30.47406 | 28.87447 | 11 | 26.91885 | 27.66133 | 31.46936 | 29.66928 | 12 | 28.46547 | 28.29937 | 28.99441 | 31.14511 | 13 | 32.42677 | 26.10410 | 29.47718 | 37.20079 | 14 | 28.84273 | 30.51801 | 32.23614 | 30.47104 | 15 | 30.75136 | 32.99922 | 28.08452 | 26.19981 | 16 | 31.25754 | 24.29473 | 35.46477 | 28.41126 | 17 | 31.24921 | 28.57954 | 35.00865 | 31.23591 | 18 | 31.41554 | 335.80049 | 33.60909 | 27.82131 | 19 | 32.20230 | 32.02005 | 32.71018 | 29.37620 | 20 | 26.91603 | 29.77775...
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...Peterson to evaluate the capability of the existing equipment used in the process. He proceeded to obtain eighteen random samples and the results of these samples were put in a table. His subsequent conclusion after analyzing the data would be that the process was not capable. This was on the basis of the width specification of 1.44 cm. Given the ambition that the company had, of introducing the new product, using the same equipment, this analysis proved a major setback. This is despite the fact that the Production Manager had hoped that the new product would have helped to ensure that the company ran on close to full capacity. Even more disappointing was the fact that the company had had a significant amount of its capital expenditure freeze. The cost of equipment would have seen the company folk out many times that amount. In a bid to obtain different and desired results, the assistant and his crew decided to different settings. However, the new settings were not effective in producing the desired results. As the Production Manager consulted the expertise of a professor with vast knowledge in the field, she was advised to undertake the same evaluation after obtaining a new sample, with more samples and an even much smaller sample size. Twenty seven samples each bearing five observations, were used for this evaluation that sought to determine the capability of the equipment to handle the production process and making of the new product. In this article, we evaluate the methods...
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...Process Analysis The main duty of the Central Lab is to collect samples and to conduct test on the samples. There are 7 stages in the process: collection, processing, separation, distribution, testing, communication and storage & retesting. The following is the flow diagram of the whole process. In order to analyze the process and find out certain solution for LAA to improve their service, this diagram is very important for us. We assume that the time for nurse to take the samples to different areas is negligible. Also, we assume that the only factors which affect the processing time are the employees. Other kind of resources such as computers, trays, carts and testing equipment will be served as many as the lab needs. Inputs and Outputs of the process: Inputs: samples from 3 different resources Relevant resources: staffs (part-time workers and full-time workers) Outputs: testing results. According to the process explanation, the processes of each stage are listed as below: Processing: Samples collected at the central lab were taken by a nurse to the sample processing area. Two Full time workers and two part-time workers took the responsibility of preparing the paperwork and barcode labels. Separation: About 50% of the samples which require more than one test will be sent to separation department. The rest of the samples will be directly distributed to different departments. There are two full-time and three pert-time staff in this department. Each sample...
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...Observation (in.) Sample Number 1 2 3 4 R x 1 0.604 0.612 0.588 0.600 0.024 0.601 2 0.579 0.601 0.607 0.603 0.028 0.598 3 0.581 0.570 0.585 0.592 0.022 0.582 4 0.620 0.605 0.595 0.588 0.032 0.602 5 0.590 0.614 0.608 0.604 0.024 0.604 6 0.585 0.583 0.617 0.579 0.038 0.591 Average 0.028 0.596 Compute the range of each sample by subtracting the lowest value from the highest value. For example, in sample 1 the range is 0.612 – 0.588 = 0.024 in., and as shown in the table, R = 0.028. Control charts for variables R chart UCLR = D₄R = 2.282 (0.028) = 0.064 LCLR = D₃R = 0 (0.028) = 0 Where R = average of several past R values and the central line of the control chart. D₃, D₄ = constants that provide three standard deviation limit for the given sample size. Plot the ranges on the R-chart, as shown in Figure 1. None of the sample ranges fall outside the control limits, so the process variability is in statistical control. Figure 1: R-Chart Control charts for variables x chart UCLx = x + A₂ R = 0.596 + 0.729 (0.028) = 0.616 LCLx = x + A₂ R = 0.596 – 0.729 (0.028) = 0.576 Where x = central line of the control chart, which can be either the average of past sample means or a target value set for the process. A₂ = constants that provide three standard deviation limit for the sample mean. Plot the ranges on the x-chart, as shown in Figure 2. None of the sample means fall outside the...
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...Quality Associates with a sample of 800 observations that were taken during a time when the client's process was operating satisfactorily. The sample standard deviation for these data was .21, hence, the population standard deviation was assumed to be .21. Quality Associates then suggested that random samples of size 30 be taken periodically to monitor the process on an ongoing basis. By analyzing the new samples, the client could quickly learn whether the process was operating satisfactorily. When the process was not operating satisfactorily, corrective action could be taken to eliminate the problem. The design specification indicated that the mean for the process should be 12. The hypothesis test suggested by Quality Associates follows: H0: μ=12 Ha: μ≠ 12 Corrective action will be taken when H0 is rejected. Samples collected during the first day of operation of the new statistical process-control procedure are in the file Quality.xls. The URL to this dataset is A. Conduct a hypothesis test for each sample at the .01 level of significance and determine what action, if any should be taken, Answer H0: μ=12 Ha: μ≠ 12 Test Statistic used is Z test Decision rule: Reject null hypothesis, if the value of test statistic is greater the critical value. Details Sample 1 Z Test of Hypothesis for the Mean Data Null Hypothesis μ= 12 Level of Significance 0.01 Population Standard Deviation 0.21 Sample Size 30 Sample Mean 11.96 Intermediate...
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...Assurance & Scientific Support, and Archiving.” (Quality Associates Incorporated) They advise their clients about sampling and statistical procedures that can be used to control their manufacturing processes. The data required for the study giving to QA from the client, a sample of 800 observations taken during a time in which that client’s process was operating satisfactorily. The sample standard deviation was 0.21 and population standard deviation was assumed to be 0.21. QA suggested taking random samples of size 30 occasionally to monitor the process on an ongoing basis. The client could quickly learn whether the process was operation reasonably and if not, corrective action could be taken to remove the problem. The design specification indicated the mean for the process should be 12. The hypothesis test suggested by Quality Associates follows. H0: u = 12 H1: u ≠ 12 Corrective action will be taken any time H0 is rejected. Conducting the hypothesis test for each sample The population of interest is 800 and each of four samples, each of size 30, collected at hourly intervals during the first day of operation of the new statistical control procedure. The two tables below shows the output of one-sample statistics test that shows the...
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...shown below: Sample 1 Sample 2 Sample 3 Sample 4 Sample Size 30 30 30 30 Mean 11.959 12.029 11.889 12.081 Standard Deviation 0.220 0.220 0.207 0.206 Level of Significance (alpha) 0.010 0.010 0.010 0.010 Critical Value (lower tail) -2.576 -2.576 -2.576 -2.576 Critical Value (upper tail) 2.576 2.576 2.576 2.576 Hypothesized value 12 12 12 12 Standard Error 0.040 0.040 0.038 0.038 Test Statistic -1.027 0.713 -2.935 2.161 p-value 0.304 0.476 0.003 0.031 Only sample 3 leads to the rejection of the hypothesis H0: µ = 12. Thus, corrective action is warranted for sample 3. The other samples indicate H0 cannot be rejected and thus from all we can tell, the process is operating satisfactorily. Sample 3 with = 11.89 shows the process is operating below the desired mean. Sample 4 with = 12.08 is on the high side, but the p-value of .03 is not sufficient to reject H0. 2. The sample standard deviations for all four samples are in the .20 to .22 range. It appears that the process population standard deviation assumption of .21 is good. 3. With α = .01, z.005 = 2.576. Using the standard error of the mean =0.0383, the upper and lower control limits are computed as follows: Upper Control Limit = 12 + 2.576 (0.0383) = 12.0987 Lower Control Limit = 12 - 2.576 (0.0383) = 11.9013 As long as a sample mean is between these two limits, the process is in control and no corrective action is required. Note that sample 3 with a mean of...
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...case study with Hot Shot Plastics company in which statistical process control (SPC) with variable measurements using X bar and R control charts is used to determine whether the process variability is in control. Sample data are utilized to demonstrate how to use X bar and R control charts to check if all the sample points are within the control limits. Patterns on the control charts are analyzed to understand the possible reasons that the process is out of control. Keywords: [control charts, statistical process control, patterns] Statistical Control of Hot Shot Plastic Keychains Hot Shot Plastics is a company that produces plastic keychains. During production of plastic keychains, Hot Shot Plastics first molds the plastic material and then trims it to the required shape. The edge quality of the keychains produced is determined by the curetimes during the molding process. The curetime is the time it takes for the plastic to cool. To ensure good quality plastic keychains, Hot Shot Plastics needs to maintain a process that yields accurate and precise curetimes. It is more desirable for the curetimes to be consistent among samples. When the curetimes are repeatable and there is less variability among samples’ curetimes, the process is deemed to be accurate. The R control chart is intended to show the accuracy of the curetimes. In addition, when the curetimes are close to the desired target curetime, the process is deemed to be precise. The X bar control chart is intended to...
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...1. Why is DAV using SPC? What are the primary challenges in applying Statistical Process Control to a service industry compared to manufacturing? SPC is a scientific approach to measure and improve the efficiency of existing processes. The way it works is: a) Fixing the control limits or the guardrails for the processes that one wants to measure. (In terms of how accurate one wants the outcome of a process to be) b) Measuring random samples (random being the key) of existing processes (measure the accuracy or the time taken to service insurance customers, essentially pick the process area to measure) to find the sample mean, and variance within the process. c) Post the measurement phase, come the execution phase where one finds out the changes that need to be made in the existing process to ensure that the accuracy stays within the specified control limits. Unlike in manufacturing, where it’s easy to distinguish what is the “right” way of doing things, and the focus is more on improving the manufacturing process, in the services, the “right” way of doing things is defined by the people and it’s often subjective. More specifically: 1) The same SPC cannot be applied on a blanket scale to every team irrespective of how efficient they already are or how difficult objectifying their work as “good” work is. 2) The definition of right and wrong can quickly become very subjective based on different perspectives of individuals. 3) All teams cannot be measured...
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...that would enhance its’ services. The team had some access to Customer Satisfaction Questionnaires and Interviews that were carefully developed to handle patients’ feedback and complaints in addition to some observations’ outcome. It is apparent that KHCC Lab enjoys a good to very good customer satisfaction in most aspects; nevertheless the major drawbacks were the delays and repetitive activities. As we went through the process and analyzed the workflow utilizing flowcharts, and control charts, we concluded that some functions are working perfectly and others need a little refinement. In conclusion, the team members identified two areas of concern; the workflow and the layout. Therefore the processes should be revisited; a new layout is to be redesigned to improve efficiency and patient’s satisfaction. In addition to the above the Lab must also eliminate or improve their blood specimen rejection problem, which is considered to be a costly problem in the long run; with our OM Pareto analysis we noticed that inadequate sample volume and Hemolysed sample are the...
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...Summary Seattle Concrete Company (SCC) produces bags of concrete mix for its customers. These bags have a stated weight of 40 pounds per bag. Given the steep penalties for under filling bags, SCC sets a target of 41 pounds per bag to ensure under filling due to natural variations still remain above the 40 pound threshold. Historically, they have operated with a single production shift, but have recently added a second shift to meet their growing demand. Management is interested in a full analysis of their process to ensure that the control limits and capabilities are within reason, and to ensure that the addition of a second shift isn’t causing issues to their process. To accomplish this, a data set was constructed. Ten bags were tested every hour during each of the two separate eight hour shifts. This continued for five days to give us 800 observations, 400 from each shift. The samples provided were analyzed for management using statistical process control methods, control charts for attributes, and capability analysis. This included X & R control charts, P-charts, C-charts, and capability analysis. The interesting finding was that all the control charts displayed variations and fill levels completely within the limits. Also, defective bags, defined as those filled to less than 40 pounds, occurred within acceptable limits. Despite all this, the capability analysis with our chosen bounds of 40 pounds to 42 pounds failed to meet the 3σ threshold. Upon this determination...
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...MARK205 Introductory Marketing Research Week 8 Today Week 8 1. Background 2. Populations & Sampling Frames Sampling 3. Sampling Process 4. Sample Size Chapters 11 & 12 of Aaker et al. (2007) The Research Process Learning Objectives • Explain the key concepts in sampling • Understand the step in the sampling process • Identify & evaluate alternative sampling techniques • The fundamentals of determining a suitable sample size 1. Background Concepts 1. Background Concepts Key Terms Population X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X Sample Population: X X X X X Census: X X X X X X X X The set of all objects that posses some common set of characteristics X Sample: Sampling: The process of surveying a sample of the population in order to make inferences about the whole population Dr Julie Francis Autumn 2015 1 MARK205 Introductory Marketing Research Week 8 1. Background Concepts 1. Background Concepts When Would You Take a Census? When is Sampling Appropriate? • When the population is small • When the population is large e.g., Mining companies operating in QLD or owners of private jets • Information is needed from every member of the population e.g., national population census or tweets about a natural disaster • Cost of making a wrong decision is high ...
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