In industrial automation, the control and operation of factories and plants in usually performed by Programmable Logic Controllers (PLCs). As automation tasks find their way into more and more smaller application areas where it is economically not reasonable to employ, engineer and maintain a full, hardware-based PLC, a cloud-based software PLC (Soft-PLC) can serve as a Control-as-a-Service solution. In this paper, we address the question how a Soft-PLC can be augmented with cloud-required aspects such as elastic scalability and multi-tenancy. We introduce an architecture that realizes these properties and allows for the implementation of a multi-tenant, horizontally scalable Soft-PLC. Furthermore, we evaluate the most important quality attributes, i.e. Roundtrip times and scalability of our architecture based on a prototypical implementation and a case study from the building automation domain. Finally, we present lessons learned and give an outlook to further realistic scenarios for cloud-based control in industrial applications.

Under the context of Industrie 4.0 (I4.0), future production systems provide balanced operations between manufacturing flexibility and efficiency, realized in an autonomous, horizontal, and decentralized item-level production control framework. Structured interoperability via precise formulations on an appropriate degree is crucial to achieve software engineering efficiency in the system life cycle. However, selecting the degree of formalization can be challenging, as it crucially depends on the desired common understanding (semantic degree) between multiple parties. In this paper, we categorize different semantic degrees and map a set of technologies in industrial automation to their associated degrees. Furthermore, we created guidelines to assist engineers selecting appropriate semantic degrees in their design. We applied these guidelines on publicly available scenarios to examine the validity of the approach, and identified semantic elements over internally developed use cases concerning plug-and-produce.

Many tasks in factory automation can be solved with the bare knowledge of used and possible product flow paths in a plant. Unfortunately, the information about these is usually not available explicitly, but is distributed among different models and tools. We present a model that describes discrete product flow paths and aims to play a similarly important role as piping and instrumentation diagrams in process industry. The model's extensibility and its CAEX representation allow a seamless integration into the established model and tool landscapes.

Automation of tedious engineering tasks allows for more efficient plant commissioning and reconfiguration. Usage of knowledge-based systems is one possibility to solve this challenge. We present a rule-based system that is based on declarative graph database queries which have the advantage of being comprehensible by both computer scientists and engineering domain experts. The applicability of the system is verified in two engineering use-cases: the creation of function blocks for basic control and flow path monitoring. Promising results from the first use-case reveal further application fields of the system.

MOTIVATION: High-throughput-sequencing (HTS) technologies are the method of choice for screening the human genome for rare sequence variants causing susceptibility to complex diseases. Unfortunately, preparation of samples for a large number of individuals is still very cost- and labor intensive. Thus, recently, screens for rare sequence variants were carried out in samples of pooled DNA, in which equimolar amounts of DNA from multiple individuals are mixed prior to sequencing with HTS. The resulting sequence data, however, poses a bioinformatics challenge: the discrimination of sequencing errors from real sequence variants present at a low frequency in the DNA pool. RESULTS: Our method vipR uses data from multiple DNA pools in order to compensate for differences in sequencing error rates along the sequenced region. More precisely, instead of aiming at discriminating sequence variants from sequencing errors, vipR identifies sequence positions that exhibit significantly different minor allele frequencies in at least two DNA pools using the Skellam distribution. The performance of vipR was compared with three other models on data from a targeted resequencing study of the TMEM132D locus in 600 individuals distributed over four DNA pools. Performance of the methods was computed on SNPs that were also genotyped individually using a MALDI-TOF technique. On a set of 82 sequence variants, vipR achieved an average sensitivity of 0.80 at an average specificity of 0.92, thus outperforming the reference methods by at least 0.17 in specificity at comparable sensitivity. AVAILABILITY: The code of vipR is freely available via: http://sourceforge.net/projects/htsvipr/ CONTACT: [email protected].

This contribution investigates the topic ldquovirtual commissioningrdquo from an industrial point of view and proposes an evolutionary and realistic technical concept for the introduction of virtual commissioning environments. Main points of this paper are the identification and formulation of industrial requirements for the introduction of a virtual commissioning environment, a proof of commercial tools against these requirements and a proposal of an evolutionary technical concept. Finally, this paper reports first experiences about a prototypical implementation of the proposed approach.

In the ldquodigital factoryrdquo tool chain, usually only the nominal production sequence, i.e. the production process under ideal conditions, is considered and automatically converted into PLC code. However, the nominal sequence is a prominent but rather small fraction of the total PLC code. The large remaining parts, such as interlock logic, safety functions, start-up and shutdown sequences, are mostly neglected. In the approach described in this paper, the authors focus on this part of the control code and strive for a concept to automatically generate a significantly larger part of the control code of a production plant, based on plant and process information which is already available.

In optoacoustic imaging, short laser pulses irradiate highly scattering human tissue and adiabatically heat embedded absorbing structures, such as blood vessels, to generate ultrasound transients by means of the thermoelastic effect. We present an optoacoustic vascular imaging system that records these transients on the skin surface with an ultrasound transducer array and displays the images online. With a single laser pulse a complete optoacoustic B-mode image can be acquired. The optoacoustic system exploits the high intrinsic optical contrast of blood and provides high-contrast images without the need for contrast agents. The high spatial resolution of the system is determined by the acoustic propagation and is limited to the submillimeter range by our 7.5-MHz linear array transducer. A Q-switched alexandrite laser emitting short near-infrared laser pulses at a wavelength of 760 nm allows an imaging depth of a few centimeters. The system provides real-time images at frame-rates of 7.5 Hz and optionally displays the classically generated ultrasound image alongside the optoacoustic image. The functionality of the system was demonstrated in vivo on human finger, arm and leg. The proposed system combines the merits and most compelling features of optics and ultrasound in a single high-contrast vascular imaging device.

The results of an experimental study aimed at the classification of radar clutter encountered on ground-based coherent scanning radar systems used for air traffic control are presented. The clutter signals of interest are primarily those due to birds and to clouds and weather systems. A historical perspective on the radar clutter classification problem is given, and related issues are discussed. The important features of radar as a sensor in an air traffic control environment are described, and physical phenomena in radar clutter and targets, which provide the physical basis for the discrimination between the different radar clutter classes, are discussed. The feature of selection/extraction procedure, which is based on the multisegment Burg algorithm, is described. The experimental evaluation of a parametric Bayes classifier and a neural network classifier is reported.>

The authors describe a high-speed systolic-based computer system designed to process real-life radar data in near real time. At the heart of the system is a ten-cell Warp (systolic) machine. A digital recorder is used to input data to the system, and a color monitor displays the output of the processing algorithms. The system permits the processing of large volumes of radar data in real time, displays the results of advanced signal-processing algorithms, and has the effect of bringing a radar environment inside the laboratory for experimental studies or, equivalently, taking a sophisticated computer outside into an operational radar environment. The authors briefly describe research efforts built around this facility and highlight the elements of the powerful signal processing neural network software that are basic to their execution.>

A method of simultaneously resolving both range and doppler ambiguities in a pulse-doppler radar is presented. The improvements over previous techniques are that only two PRFs are required and that the same number of doppler filters in each PRF is permitted.