Lecture 3 Statistical Process Control Using Control Charts

Lecture 3 Statistical Process Control Using Control Charts

Review Apakah yang anda ketahui tentang peta kendali / Shewhart control chart? Jelaskan pentingnya diagram pareto dalam proses perbaikan kualitas?

Outline Pengantar Penyebab Variasi Statistik Dasar untuk Control Charts Pemilihan Subkelompok rasional Analisis Pola pada Control Chart Pemeliharaan Control Chart

Introduction Proses kontrol statistik (Statistical process control) adalah kumpulan alat yang bila digunakan bersama-sama dapat menghasilkan stabilitas proses dan pengurangan variabilitas Control Chart: alat grafisuntuk memonitor aktivitas dari proses yang sedang berlangsung

Introduction Manfaat menggunakan control chart Ketika untuk mengambil tindakan korektif Jenis tindakan perbaikan yang diperlukan Ketika meninggalkan proses sendirian Kapabilitas proses Kemungkinan sarana peningkatan kualitas Cara menetapkan spesifikasi produk

Cause of Variation Penyebab variasi Chance Cause melekat proses Sesuatu (sebagai variasi alami dalam proses ) Assignable Cause Sesuatu yang dapat diidentifikasi ditentukan Contoh: alat yang salah, kesalahan operator

Cause of Variation Chance and Assignable Causes of Quality Variation Sebuah proses yang hanya disebabkan chance causes, proses tersebut dikatakan dalam pengendalian statistik. Alam variabilitas atau kebisingan latar belakang. Fluktuasi Sebuah proses yang beroperasi di hadapan penyebab dialihkan dikatakan di luar kendali. Misalnya Kesalahan operator, bahan baku yang rusak, pengaturan yang tidak tepat. Tujuan akhirnya SPC adalah pengurangan atau penghapusan variabilitas dalam proses identifikasi penyebab dialihkan. A process that is operating with only chance causes of variation present is said to be in statistical control. Natural

Statistical Basis for Control Charts Basic Principles Assumed to have approximately normal distribution Control limits : 99.74 % ( 3σ limits ) A control chart : on line process control Making inference

Statistical Basis for Control Charts Selection of Control Limits Let θ represent a quality characteristic of interest and represent an estimate of θ CL = E ( ˆ θ ) ( ˆ θ ) ( ˆ θ ) UCL = E + k SD ( ˆ θ ) ( ˆ θ ) LCL = E k SD If k = 3 0.0026 of a sample statistic falling outside

Statistical Basis for Control Charts Errors in making inference from control chart Type I : process is out of control when it is actually in control Type II : process is in control when it is really out of control Effect of control limits on errors in making inference Warning limit Usually 2 standard deviation Effect of sample size on control limits Influence in standard deviation

Statistical Basis for Control Charts Basic Principles A typical control chart has control limits set at values such that if the process is in control, nearly all points will lie between the upper control limit (UCL) and the lower control limit (LCL).

Statistical Basis for Control Charts A control chart contains A center line An upper control limit A lower control limit A point that plots within the control limits indicates the process is in control No action is necessary A point that plots outside the control limits is evidence that the process is out of control Investigation and corrective action are required to find and eliminate assignable cause(s) There is a close connection between control charts and hypothesis testing

Photolithography Example Important quality characteristic in hard bake is resist flow width Process is monitored by average flow width Sample of 5 wafers Process mean is 1.5 microns Process standard deviation is 0.15 microns Note that all plotted points fall inside the control limits Process is considered to be in statistical control

Selection of rational Subgroups The premise : chosen is such manner that the variation within it is considered to due only to chance causes. Basis : Time order Two approaches ( Besterfield, 1990 ) Instance of time method Period of time method Subgroup Size ( the number of items in each group ) Frequency of sampling

Selection of rational Subgroups Subgroups or samples should be selected so that if assignable causes are present, the chance for differences between subgroups will be maximized, while the chance for differences due to these assignable causes within a subgroup will be minimized.

Selection of rational Subgroups Selection of Rational Subgroups Two general approaches to constructing rational subgroups. Select consecutive units of production. Each sample consists of units that were produced at the same time (or as closely together as possible) Provides a snapshot of the process. Effective at detecting process shifts.

Select a random sample over the entire sampling interval. Often used to make decisions about the acceptance of all units of product that have been produced since the last sample. Can be effective at detecting if the mean has wandered out-of-control and then back in-control.

Analysis of Patterns in Control Chart Five Rules for identifying an out-of-control process 1. A single point outside the control limits 2. Two out of three consecutive points fall outside the 2σ warning limits on the same side 3. Four out of five consecutive points fall beyond the 1σ warning limits on the same side 4. Eight or more consecutive points fall to one side 5. A run of eight or more consecutive points up, down, above or below the CL, or above or bellow the median

Analysis of Patterns in Control Chart Nonrandom patterns can indicate out-ofcontrol conditions Patterns such as cycles, trends, are often of considerable diagnostic value (more about this in Chapter 5) Look for runs - this is a sequence of observations of the same type (all above the center line, or all below the center line) Runs of say 8 observations or more could indicate an out-of-control situation. Run up: a series of observations are increasing Run down: a series of observations are decreasing

An x chart with a nonrandom, up-run, down-run patterns

An x chart with a cyclic pattern

Analysis of Patterns in Control Chart Interpretation of Plots ( Non random pattern ) Determination of causes associated with out-of-control points Require a thorough knowledge of the process and the sensitivity of the output quality characteristic to the process parameters The pattern and associated causes Change in the level of the plotted pattern ( a jump ) ( change quality raw material, change operator, failure component ) Trend in the plotted pattern ( tool wear, change in pressure ) Cyclic behavior in the plotted pattern ( seasonal effects of quality, operator fatigue ) Concentration of points near the control limits ( two or more operator plotted on the same chart, different production method )

Maintenance of Control Chart Proper placement of the control charts on the shop floor is important easy to access The control chart should draw the attention and curiosity of everyone involved

Quiz 1. What are benefits of using control chart? 2. Explain the different between chance causes and assignable causes? give example of each? 3. How are rational subgroups selected? explain the importance of this in the total quality systems approach? 4. 5-13?

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