| 1. |
- Conseil-Gudla, Helene, et al.
(författare)
-
Transient risk of water layer formation on PCBAs in different climates: Climate data analysis and experimental study
- 2022
-
Ingår i: Microelectronics and reliability. - : Elsevier. - 0026-2714 .- 1872-941X. ; 136
-
Tidskriftsartikel (refereegranskat)abstract
- The reliability of electronic devices depends on the environmental loads at which they are exposed. Climatic conditions vary greatly from one geographical location to another (from hot and humid to cold and dry areas), and the temperature and humidity vary from season to season and from day to day. High levels of temperature and relative humidity mean high water content in the air, but saturated conditions (i.e. 100 % RH) can also be reached at low temperatures. This paper analyses the relationship between temperature, dew point temperature, their difference (here called ΔT), and occurrence and time period of dew point closeness to temperature on transient condensation effects on electronics.This paper has two parts: (i) Data analysis of typical climate profiles within the different zones of the Köppen -Geiger classification to pick up conditions where ΔT is very low (for example ≤0.4 °C). Various summary statistics of these events are calculated in order to assess the temperature at which these events happen, their durations and their frequency and (ii) Empirical investigation of the effect of ΔT ≤ 0.4 °C on the reliability of electronics by mimicking an electronic device, for which the time period of the ΔT is varied in one set of experiments, and the ambient temperature is varied in the other. The effect of the packaging of the electronics is also studied in this section.The statistical study of the climate profiles shows that the transient events (ΔT ≤ 0.4 °C) occur in almost every location, at different temperature levels, with a duration of at least one observation (where observations were hourly in the database). The experimental results show that presence of the enclosure, cleanliness and bigger pitch size reduce the levels of leakage current, while similar high levels of leakage current are observed for the different durations of the transient events, indicating that these climatic transient conditions can have a big impact on the electronics reliability.
|
|
| 2. |
- Kulahci, Murat, et al.
(författare)
-
Experiences with big data : Accounts from a data scientist’s perspective
- 2020
-
Ingår i: Quality Engineering. - : Taylor & Francis. - 0898-2112 .- 1532-4222. ; 32:4, s. 529-542
-
Tidskriftsartikel (refereegranskat)abstract
- Manufacturing has been rejuvenated by automation and digitalization. This has brought forth the new industrial era also called Industry 4.0. During the last few years, we have collaborated with companies from various industries that have all been going through this transformation. Through these collaborations, we have collected numerous examples of (sometimes troublesome) experiences with Big Data applications of production analytics. These experiences reflect the current state of production data and the challenges it poses. Our goal in this paper is to share those experiences and lessons learned in dealing with practical issues from data acquisition to data management and finally to data analytics.
|
|
| 3. |
- Kulahci, Murat, et al.
(författare)
-
Rejoinder
- 2020
-
Ingår i: Quality Engineering. - : Taylor & Francis. - 0898-2112 .- 1532-4222. ; 32:4, s. 563-565
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
|
|
| 4. |
- Spooner, Max, et al.
(författare)
-
A climate classification for corrosion control in electronic system design
- 2022
-
Ingår i: Machine Learning with Applications. - : Elsevier. - 2666-8270. ; 9
-
Tidskriftsartikel (refereegranskat)abstract
- Climate factors such as humidity and temperature have a significant impact on the corrosion reliability of electronic products. Given the huge geographical variability in climate conditions globally, a climate classification is a useful tool that simplifies the problem of considering climate when designing electronics packaging. Most current guidelines for electronic product design rely on the Köppen-Geiger classification first developed by Köppen over a century ago. Köppen devised a set of heuristics to separate climates to match different vegetation types. These climate classes are unlikely to be the optimal for electronic product design. This paper presents a new climate classification using parameters important for corrosion reliability of electronics. The classification is based on real climate data measured every 3 h during a 5-year period at over 9000 locations globally. A key step is defining relevant features of climate affecting corrosion in electronics. Features related to temperature are defined, but also the amount of time that the difference between Temperature and Dew Point is less than 1, 2 or 3 ℃. These features relate to the risk of condensation in electronic products. The features are defined such that diurnal, seasonal and yearly variation is taken into account. The locations are then clustered using K-means clustering to obtain the relevant climate classes. This data-driven classification, based on key features for corrosion reliability of electronics, will be a useful aid for product design, reliability testing and lifetime estimation.
|
|
| 5. |
- Spooner, Max, et al.
(författare)
-
Harvest time prediction for batch processes
- 2018
-
Ingår i: Computers and Chemical Engineering. - : Elsevier. - 0098-1354 .- 1873-4375. ; 117, s. 32-41
-
Tidskriftsartikel (refereegranskat)abstract
- Batch processes usually exhibit variation in the time at which individual batches are stopped (referred to as the harvest time). Harvest time is based on the occurrence of some criterion and there may be great uncertainty as to when this criterion will be satisfied. This uncertainty increases the difficulty of scheduling downstream operations and results in fewer completed batches per day. A real case study is presented of a bacteria fermentation process. We consider the problem of predicting the harvest time of a batch in advance to reduce variation and improving batch quality. Lasso regression is used to obtain an interpretable model for predicting the harvest time at an early stage in the batch. A novel method for updating the harvest time predictions as a batch progresses is presented, based on information obtained from online alignment using dynamic time warping.
|
|
| 6. |
- Spooner, Max, et al.
(författare)
-
Monitoring batch processes with dynamic time warping and k-nearest neighbours
- 2018
-
Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 183, s. 102-112
-
Tidskriftsartikel (refereegranskat)abstract
- A novel data driven approach to batch process monitoring is presented, which combines the k-Nearest Neighbour rule with the dynamic time warping (DTW) distance. This online method (DTW-NN) calculates the DTW distance between an ongoing batch, and each batch in a reference database of batches produced under normal operating conditions (NOC). The sum of the k smallest DTW distances is monitored. If a fault occurs in the ongoing batch, then this distance increases and an alarm is generated. The monitoring statistic is easy to interpret, being a direct measure of similarity of the ongoing batch to its nearest NOC predecessors and the method makes no distributional assumptions regarding normal operating conditions. DTW-NN is applied to four extensive datasets from simulated batch production of penicillin, and tested on a wide variety of fault types, magnitudes and onset times. Performance of DTW-NN is contrasted with a benchmark multiway PCA approach, and DTW-NN is shown to perform particularly well when there is clustering of batches under NOC.
|
|
| 7. |
- Spooner, Max, et al.
(författare)
-
Selecting local constraint for alignment of batch process data with dynamic time warping
- 2017
-
Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 167, s. 161-170
-
Tidskriftsartikel (refereegranskat)abstract
- There are two key reasons for aligning batch process data. The first is to obtain same-length batches so that standard methods of analysis may be applied, whilst the second reason is to synchronise events that take place during each batch so that the same event is associated with the same observation number for every batch. Dynamic time warping has been shown to be an effective method for meeting these objectives. This is based on a dynamic programming algorithm that aligns a batch to a reference batch, by stretching and compressing its local time dimension. The resulting ”warping function” may be interpreted as a progress signature of the batch which may be appended to the aligned data for further analysis. For the warping function to be a realistic reflection of the progress of a batch, it is necessary to impose some constraints on the dynamic time warping algorithm, to avoid an alignment which is too aggressive and which contains pathological warping. Previous work has focused on addressing this issue using global constraints. In this work, we investigate the use of local constraints in dynamic time warping and define criteria for evaluating the degree of time distortion and variable synchronisation obtained. A local constraint scheme is extended to include constraints not previously considered, and a novel method for selecting the optimal local constraint with respect to the two criteria is proposed. For illustration, the method is applied to real data from an industrial bacteria fermentation process.
|
|
