scholarly journals Supercollider program plan. Phase 1

10.2172/88538 ◽  
1985 ◽  
Author(s):  
Keyword(s):  
Phase 1 ◽  
Program Plan ◽  
Plan Phase

scholarly journals Penerapan Model Pembelajaran Savi Untuk Meningkatkan Hasil Belajar Forehand Drive Permainan Tenis Meja Mahasiswa Prodi PJKR Semester Ganjil FIK-Unimed

2017 ◽  
Vol 2 (1) ◽  
pp. 66
Author(s):  
Zulpikar Ilham
Keyword(s):  
Learning Outcomes ◽  
Phase 1 ◽  
Learning Model ◽  
Difficulty Level ◽  
Table Tennis ◽  
Learning Program ◽  
Research Activity ◽  
Resource Requirement ◽  
Program Plan ◽  
The Impact

This study is intended to examine the impact of the application of SAVI learning model to improve learning outcomes forehand table Tennis drive. With this research this study aims to determine the impact of the application of SAVI learning model to improve learning outcomes forehand table tennis drive. With this research is expected to improve learning results forehand table tennis drive on students majoring in PJKR FIK-Unimed. Application of this SAVI learning model will help lecturers to determine the appropriate learning stages of the difficulty level, so that the students can master the technique well and also encourage improving learning outcomes. This study uses action research methods developed by Kemis. The research activity plan is conducted with 2 cycles with each cycle consisting of 4 stages; (1) phase 1, do the planning. In this planning the researcher performs the initial test, identification of resource requirement, programming of learning program plan and determination of achievement indicator, (2) second stage, implementation. At this stage, a step-by-step learning process is based on the learning program plan, (3) third stage, observation. At this stage observation is attached to each exercise and perform tests and measurements, (4) fourth stage, do reflection. Reflection is done to find some obstacles and problems and then become the basis for determining activities in the second cycle. Output target in this research is minimal journal with ISSN.

scholarly journals Modelling of an Additive 3D-Printing Process Based on Design of Experiments Methodology

2020 ◽  
Vol 24 (1) ◽  
pp. 128
Author(s):  
José Alberto Eguren ◽  
Aritz Esnaola ◽  
Gorka Unzueta
Keyword(s):  
Experimental Study ◽  
3D Printing ◽  
Design Of Experiments ◽  
Phase 1 ◽  
Statistical Testing ◽  
Phase 2 ◽  
High Quality ◽  
Phase 3 ◽  
Industrial Sectors ◽  
Plan Phase

<p><strong>Purpose:</strong> The implementation of additive manufacturing (AM) or 3D-printer manufacturing for technical prototyping, preproduction series and short production series can bring benefits in terms of reducing cost and time to market in product development. These technologies are beginning to be applied in different industrial sectors and have a great possibility of development. As these technologies are still in development, there is a need to define the capacity of the 3D machines to establish minimum standards for producing high-quality parts.</p><p><strong>Methodology/Approach:</strong> The proposed methodology is based on a design of experiments (DOE) approach, which serves as a guide for engineers when it comes to executing any experimental study. The following steps were followed (Unzueta et al., 2019): Phase 1: define; Phase 2: measure; Phase 3: plan; Phase 4: execute experimentation; Phase 5: analyse the results; Phase 6: improve via confirmation experiments; Phases 7-8: control and standardise.</p><p><strong>Findings:</strong> The proposed methodology is based on a design of experiments (DOE) approach, which serves as a guide for engineers when it comes to executing any experimental study. The following steps were followed (Unzueta et al., 2019): Phase 1: define; Phase 2: measure; Phase 3: plan; Phase 4: execute experimentation; Phase 5: analyse the results; Phase 6: improve via confirmation experiments; Phases 7-8: control and standardise.</p><strong>Originality/Value of paper:</strong> This study uses a methodological approach to demonstrate how the 3D printing technology can be enriched with statistical testing techniques (DOE). It defines numerical prediction models to obtain high-quality parts with a new AM technology, using a planning process with a minimum amount of experimentation.

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