Design and application of dual-EWMA scheme for anomaly detection in injection moulding process
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Article number | 106132 |
Journal / Publication | Computers and Industrial Engineering |
Volume | 138 |
Online published | 21 Oct 2019 |
Publication status | Published - Dec 2019 |
Link(s)
Abstract
Plastic injection moulding is one of the very challenging processes to yield products with good quality and low cost. This study presents an optimization model for designing an exponentially weighted moving average (EWMA) scheme consisting of two individual EWMA schemes (called dual-EWMA scheme) for efficient monitoring of a range of mean shifts in an injection moulding process producing plastic parts. The optimization design is conducted under the constraints of inspection resources (labor equipped with measurement instrumentation) and false alarm rate, which ensures that no extra manpower will be needed and the false alarm rate of the charting scheme will not be increased. The effectiveness of the optimal dual-EWMA scheme is investigated through a 23 factorial design considering different scenarios, which shows that the proposed charting scheme is significantly superior to its main competitor, the conventional dual-EWMA scheme, as well as other schemes. The impact of design specifications on the effectiveness of the proposed scheme is analyzed through a sensitivity study. The design and implementation of the proposed scheme are demonstrated through a case study. Finally, a design table is presented to ease the application of the proposed scheme in practice.
Research Area(s)
- Control chart, Dual-EWMA scheme, Injection moulding process, Statistical process control
Citation Format(s)
Design and application of dual-EWMA scheme for anomaly detection in injection moulding process. / Shamsuzzaman, Mohammad; Haridy, Salah; Maged, Ahmed et al.
In: Computers and Industrial Engineering, Vol. 138, 106132, 12.2019.
In: Computers and Industrial Engineering, Vol. 138, 106132, 12.2019.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review