DESAIN EKSPERIMEN INTRODUCTION - debrina.lecture.ub.ac.iddebrina.lecture.ub.ac.id/files/2018/02/1-Introduction.pdfDESAIN EKSPERIMEN INTRODUCTION ... – Process characterization &

DESAINEKSPERIMENINTRODUCTION

SemesterGenap2017/2018JurusanTeknikIndustriUniversitasBrawijaya

OUTLINE •  Introduction to DOX •  Four Eras in the History of DOX •  Engineering Experiments •  Typical Applications of Experimental Design •  Strategy of Experimentation •  Factorial Design •  Factorial Designs with Several Factors and Fractional

Factorial •  The Basic Principles of DOX •  Planning, Conducting & Analyzing an Experiment

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Introduction to DOX (1/2)

•  An experiment is a test or a series of tests •  Experiments are used widely in the engineering world

–  Process characterization & optimization –  Evaluation of material properties –  Product design & development –  Component & system tolerance determination

•  “All experiments are designed experiments, some are poorly designed, some are well-designed”

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Introduction to DOX (2/2) •  Experimentation is a vital part of scientific (or

engineering) method •  For any experiment, questions to be asked:

•  Are only these methods available? •  Are there any other factors that might affect the results? •  How many samples are needed for the experiment? •  How should the samples be assigned to each experiment? •  What is the order that the data should be collected? •  What method of data analysis should be used? •  What difference in average observed results between method,

material, machines,…?

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Four Eras in the History of DOX •  The agricultural origins, 1918 – 1940s

–  W.S. Gossett and the t-test (1908) –  R. A. Fisher & his co-workers –  Profound impact on agricultural science –  Factorial designs, ANOVA

•  The first industrial era, 1951 – late 1970s –  Box & Wilson, response surfaces –  Applications in the chemical & process industries

•  The second industrial era, late 1970s – 1990 –  Quality improvement initiatives in many companies –  Taguchi and robust parameter design, process

robustness •  The modern era, beginning circa 1990

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R. A. Fisher (1890 – 1962)

George E. P. Box

Engineering Experiments (1/2) •  In general, experiments are used to

study the process and systems. •  The process can be the combination of

operations, machines, methods, people, and other resources (often materials) that transfer some input into output that has one or more observable response variables y.

•  Some of the process variables and material properties, x1, …, xp are controllable.

•  Some of them are uncontrollable (although they may be controllable for purposes of a test).

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Engineering Experiments (2/2)

•  Determining which variables are most influential on the response y

•  Determining where to set the influential x’s so that y is almost always near the desired nominal value.

•  Determining where to set the influential x’s so that variability in y is small.

•  Determining where to set the influential x’s so that the effects of the uncontrollable variables z1, …., zq are minimized.

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Typical Applications of Experimental Design

•  Improve process yield •  Reduce variability and closer conformance to nominal or target

requirements •  Reduce development time •  Reduce overall costs •  Evaluate and compare basic design configurations •  Evaluate material alternatives •  Select design parameters •  Determine key product design parameters •  Formulate new product


Strategy of Experimentation (1/4)

•  Golf example-factor to influence the score •  Driver – oversized or regular •  Ball – balata or three piece •  Mode of travel — walking or riding a

golf cart •  Beverage – water or beer •  …….



•  “Best-guess” experiments –  Used a lot –  More successful than you might suspect, but there are

disadvantages…

•  One-factor-at-a-time (OFAT) experiments –  Sometimes associated with the “scientific” or “engineering”

method –  Devastated by interaction, also very inefficient

•  Statistically designed experiments –  Based on Fisher’s factorial concept

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Factorial Design (1/3)

•  In a factorial experiment, all possible combinations of factor levels are tested

•  The golf experiment: –  Type of driver –  Type of ball –  Walking vs. riding –  Type of beverage –  Time of round –  Weather –  Type of golf spike –  Etc, etc, etc






Factorial Designs with Several Factors


Factorial Designs with Several Factors A Fractional Factorial

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TheBasicPrinciplesofDOX


Randomization Running the trials in an experiment in random order Notion of balancing out effects of “lurking” variables

Replication Sample size (improving precision of effect estimation, estimation of error or background noise) Replication versus repeat measurements? Replication reflects sources of variability both between runs and within runs

Blocking Dealing with nuisance factors

Planning, Conducting & Analyzing an Experiment

1.  Recognition of & statement of problem 2.  Choice of factors, levels, and ranges 3.  Selection of the response variable(s) 4.  Choice of design 5.  Conducting the experiment 6.  Statistical analysis 7.  Drawing conclusions, recommendations 8.  Get statistical thinking involved early 9.  Your non-statistical knowledge is crucial to success 10.  Pre-experimental planning (steps 1-3) vital 11.  Think and experiment sequentially (use the KISS principle)


Pre-experimental planning

Kekeliruan Eksperimen �  Menyatakan kegagalan dari dua unit eksperimen identik yang

dikenai perlakuan untuk memberikan hasil yang sama.

�  Contoh: kekeliruan waktu menjalankan eksperimen, kekeliruan pengamatan, variasi bahan eksperimen, variasi antara unit eksperimen dan pengaruh gabungan semua faktor tambahan

�  Untuk mengurangi kekeliruan dapat menggunakan bahan eksperimen yang homogen, menggunakan informasi yang sebaik-baiknya tentang variabel yang telah ditentukan dengan tepat, melakukan eksperimen dengan teliti, menggunakan DE yang lebih efisien


Tambahan:

Efek dan interaksi

•  Dalam keperluan desain eksperimen, variabel bebas dinamakan faktor, dan nilai-nilai atau klasifikasi-klasifikasi dari sebuah faktor dinamakan taraf faktor.

•  Faktor-faktor dinyatakan dengan huruf kecil a, b, c, d, dst.., sedangkan taraf faktor dinyatakan dengan angka 1, 2, 3, dst yang dituliskan sebagai indeks untuk faktor yang bersangkutan.


Tambahan:

KontrolLokal

Pengelompokan

•  Penempatan sekumpulan unit eksperimen ke dalam kelompok-kelompok agar kelompok yang berbeda memungkinkan untuk mendapatkan perlakuan yang berbeda pula.

•  Contohnya ketika meneliti pengaruh tiga macam cara penyampaian materi terhadap mahasiswa. Terdapat 11 mahasiswa, yang dibagi menjadi 3 kelompok, (4-4-3). Penempatan atau pemilihan mahasiswa ke dalam kelompok-kelompok dilakukan secara acak. Masing-masing kelompok diberikan materi dengan cara berbeda (A-B-C)

Pemblokan

•  Pengalokasian unit-unit eksperimen ke dalam blok sehingga unit-unit dalam blok secara relatif bersifat homogen sedangkan sebagian besar dari variasi yang dapat diperkirakan di antara unit-unit telah terbaur dengan blok.

•  Variasi yang dapat diduga tidak menjadi bagian daripada kekeliruan eksperimen, sehingga desain lebih efisien.

•  Contohnya:: Ada 12 komponen mesin. Enam jenis X, tiga jenis Y, dan tiga jenis Z. Jenis diambil sebagai blok. Blok pertama terdiri dari 6 buah komponen jenis X. Blok kedua terdiri dari 3 buah komponen jenis Y. Blok ketiga terdiri dari 3 buah komponen jenis Z.

Penyeimbangan

• Usahamemperolehuniteksperimen,usahapengelompokan,pemblokandanpenggunaanperlakuansedemikiansehinggadihasilkankonfigurasiformasiyangseimbang


Tambahan:

Documents

DESAIN EKSPERIMEN INTRODUCTION - debrina.lecture.ub.ac.iddebrina.lecture.ub.ac.id/files/2018/02/1-Introduction.pdfDESAIN EKSPERIMEN INTRODUCTION ... – Process characterization &