| Issue |
MATEC Web Conf.
Volume 137, 2017
Modern Technologies in Manufacturing (MTeM 2017 - AMaTUC)
|
|
|---|---|---|
| Article Number | 03013 | |
| Number of page(s) | 6 | |
| Section | Machining Processes and Quality Assurance | |
| DOI | https://doi.org/10.1051/matecconf/201713703013 | |
| Published online | 22 November 2017 | |
Optimal production size with partially inspected batches
1 HIT, Holon Institute of Technology, Technology Management Faculty, 52 Golomb St. Holon, 58102, Israel
2 Technical University of Cluj Napoca, Department of Management and Economic Engineering, Cluj Napoca, Romania
* Corresponding author: sadeh@hit.ac.il
While it is desirable to manufacture and ship perfect products, in many cases it is possible to ship products even though they do not stand up to all aspects of inspections. In this study a single machine is considered, that produces m products per day and there are n parameters that each product should pass. The number of passes (b) is a decision vector. A mathematical programming approach is used in order to model and optimize the number of products to be shipped under the constraints of failures. The results can be used for predetermined manufacturing, i.e. to set a series of tests less than m for each batch of production. In addition, aspects of calculation and computation are considered since the problem involves integer variables. Numerical examples and simulation runs of the suggested model are provided along with sensitivity runs.
© The authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.