Abstract Batch processing reduces time in a business process at the expense of increasing waiting time. If this trade-off between and is not analyzed, batch can, over time, evolve into source waste process. Therefore, it valuable to analyze activities identify wastes. Identifying analyzing such wastes present analyst with improvement opportunities that, if addressed, can improve cycle efficienc...

Today, big data is generated from many sources and there is a huge demand for storing, managing, processing, and querying on big data. The MapReduce model and its counterpart open source implementation Hadoop, has proven itself as the de facto solution to big data processing. Hadoop is inherently designed for batch and high throughput processing jobs. Although Hadoop is very suitable for batch ...

This paper considers a scheduling problem for a single burn-in oven in the semiconductor manufacturing industry where the oven is a batch processing machine and each batch processing time is represented by the largest processing time among those of all the jobs contained in the batch. Each job belongs to one of the given number of families.Moreover, the release times of the jobs are di!erent fr...

We introduce the Free Factory, a platform for deploying data-intensive web services using small clusters of commodity hardware and free software. Independently administered virtual machines called Freegols give application developers the flexibility of a general purpose web server, along with access to distributed batch processing, cache and storage services. Each cluster exploits idle RAM and ...

The goal of metabolomics data pre-processing is to eliminate systematic variation, such that biologically-related metabolite signatures are detected by statistical pattern recognition. Although several methods have been developed to tackle the issue of batch-to-batch variation, each method has its advantages and disadvantages. In this study, we used a reference sample as a normalization standar...