No abstract

This paper deals with improving the lead-time performance of a large crystal manufacturer that uses a state-of-the-art commercial Enterprise Resource Planning system. Since the company encountered some limitations of the standard production planning and control (PPC) system it sought for improvements by implementing an order release mechanism based on workload control (WLC). WLC employs certain rules for releasing orders in order to maintain a certain level of work in process to achieve a certain utilisation of the production system and thus control the flow times in order to meet the required due dates of the orders. We describe the successful implementation of an order release mechanism based on the WLC concept in this make-to-stock company. The paper describes the implemented order release mechanism, the implementation process and its impact on the company's performance. We show that the core function of WLCthe order release mechanismcan be integrated successfully into an existing PPC system. Furthermore, this study highlights the applicability of WLC to a wider range of companies, especially to make-to-stock manufacturers.

Background: Molecular characters have been added in integrative taxonomic approaches in recent years. Nevertheless, taxon diagnoses are still widely restricted to morphological characters. The inclusion of molecular characters into taxon diagnoses is not only hampered by problems, such as their definition and the designation of their positions in a reference alignment, but also by the technical effort. Results: DeSignate is a tool for character-based taxon diagnoses that includes a novel ranking scheme. It detects and classifies individual and combined signature characters (diagnostic molecular characters) based on so-called character state vectors. An intuitive web application guides the user through the analysis process and provides the results at a glance. Further, formal definitions and a uniform terminology of characters are introduced. Conclusions: DeSignate facilitates the inclusion of diagnostic molecular characters and their positions to complement taxon diagnoses. Compared to previous solutions, the tool simplifies the workflow and improves reproducibility and traceability of the results.

Although many works in the database community use open data in their experimental evaluation, repeating the empirical results of previous works remains a challenge. This holds true even if the source code or binaries of the tested algorithms are available. In this paper, we argue that providing access to the raw, original datasets is not enough. Real-world datasets are rarely processed without modification. Instead, the data is adapted to the needs of the experimental evaluation in the data preparation process. We showcase that the details of the data preparation process matter and subtle differences during data conversion can have a large impact on the outcome of runtime results. We introduce a data reproducibility model, identify three levels of data reproducibility, report about our own experience, and exemplify our best practices.

No abstract