Abstract: Provided is an application of the described (or similar) decision-theoretic approaches to ensure the quality, output and timeliness of manufactured products for flexible and adaptable production systems, by determining and integrating suitable quality assurance measures which are integrated into the production process in an optimal manner. Thereby, a pareto-optimal sequence of production steps and quality assurance mechanisms are determined that provides an optimal trade-off between target product quality, production time and production costs. Since the approach is performed in an automated way, it can even be performed for flexible production scenarios down to a production of lot size I.

Abstract: A computer-implemented method for sharing differentially private reliability data in an IIoT infrastructure is provided, wherein the IIoT infrastructure includes a central computing device and at least one local computing device, comprising the steps: a. applying a differentially private algorithm on at least one processed input reliability data set solely once to add randomness to the at least one processed input reliability data set by the central computing device; or b. applying the differentially private algorithm on at least one individual input reliability data set to add randomness to the at least one individual input reliability data set by the at least one local computing device; and providing the differentially private reliability data by the at least one local computing device A corresponding computer program product and IIoT infrastructure is also provided.

Abstract: A method for controlling a technical system, wherein at least one milestone step and a plurality of intermediate steps are scheduled at respective points in time is provided. Time deviations for the intermediate steps are obtained, wherein a time deviation denotes a difference from an initial planning of a step. For the milestone step, a time deviation is determined using the time deviations of the intermediate steps. A cost function is obtained for the milestone step, wherein the cost function defines a cost value for the technical system dependent on the time deviation of the milestone step using a domain-specific language, e.g., based on a contractual requirement for the technical system. A cost value is determined for the technical system using the time deviation of the milestone step and the cost function. The technical system is controlled based on the cost value.

Abstract: Provided is an application of the described (or similar) decision-theoretic approaches to ensure the quality, output and timeliness of manufactured products for flexible and adaptable production systems, by determining and integrating suitable quality assurance measures which are integrated into the production process in an optimal manner. Thereby, a pareto-optimal sequence of production steps and quality assurance mechanisms are determined that provides an optimal trade-off between target product quality, production time and production costs. Since the approach is performed in an automated way, it can even be performed for flexible production scenarios down to a production of lot size I.

Abstract: The following refers to a computer-implemented approach for evaluation of contractual requirements in view of a technical railway system, namely whether the latter complies with the requirements. The technical railway system and is modeled in case of non-compliance the system is modeled and contractual requirements are modeled in one common model. The generated model is analyzed in order to calculate control instructions for matching the same.

Abstract: A method for determining a reliability parameter of a new technical system based on assigned failure parameters of m known technical systems is provided, wherein the new technical system comprises n1 devices of a first type, n2 devices of a second type, . . . , and nk devices of a k-th type; an i-th known technical system out of the m known technical systems, with 1?i?m, has an assigned failure parameter pi and comprises ni1 devices of the first type, ni2 devices of the second type, . . . , and nik devices of the k-th type; and individual failure information relating to the devices of the first to k-th type is initially unknown.

Abstract: A computer-implemented approach with methods, systems and programs for automatically optimizing a set of contractual template instances for a contract for a technical system between contracting parties is provided. The method accesses a modelling unit, which is adapted to provide modelled contracts with a set of contractual templates, wherein each contractual template has a set of parameters and a set of constraints. A synthesizer is accessed for synthesizing a set of contractual template instances which comply with the received constraints values. Finally, an evaluation engine is accessed with received optimization criteria for optimizing the set of synthesized contractual template instances in order to calculate at least one optimized contractual template instance as a result.

Abstract: The following refers to a computer-implemented approach for evaluation of contractual requirements in view of a technical railway system, namely whether the latter complies with the requirements. The technical railway system and is modeled in case of non-compliance the system is modeled and contractual requirements are modeled in one common model. The generated model is analyzed in order to calculate control instructions for matching the same.

Abstract: A method for analyzing functional failures of a technical system using a processor to compute a meta data model, including the following steps is provided. A first step of gathering at least one failure mode for each component of a system dataset describing the technical system. A second step of associating at least one effect and at least one related maintenance task with each failure mode to mitigate and/or to dissolve the effect in the meta data model. A third step of computing failure probabilities of said technical system based on the meta data model, while the technical system is in the specific situation.

Abstract: A method for determining a reliability parameter of a new technical system based on assigned failure parameters of m known technical systems is provided, wherein the new technical system comprises n1 devices of a first type, n2 devices of a second type, . . . , and nk devices of a k-th type; an i-th known technical system out of the m known technical systems, with 1?i?m, has an assigned failure parameter pi and comprises ni1 devices of the first type, ni2 devices of the second type, . . . , and nik devices of the k-th type; and individual failure information relating to the devices of the first to k-th type is initially unknown.

Abstract: A method for analyzing functional failures of a technical system using a processor to compute a meta data model, including the following steps is provided. A first step of gathering at least one failure mode for each component of a system dataset describing the technical system. A second step of associating at least one effect and at least one related maintenance task with each failure mode to mitigate and/or to dissolve the effect in the meta data model. A third step of computing failure probabilities of said technical system based on the meta data model, while the technical system is in the specific situation.

Abstract: A method, apparatus and computer program product for the conversion of at least one reliability model of a technical system to a Bayesian network model for assisting in the system's failure diagnostics, has the steps of creating a structure of a Bayesian network using information from at least one reliability model of the technical system, creating parameters of the Bayesian network using information from the reliability model of the technical system, the Bayesian network model having a plurality of observation nodes, obtaining information about the plurality of observation nodes from a list of observations that augments information contained in the reliability model of the technical system, and inserting the observation nodes into the created structure of the Bayesian network.

Abstract: A method, apparatus and computer program product for the conversion of at least one reliability model of a technical system to a Bayesian network model for assisting in the system's failure diagnostics, has the steps of creating a structure of a Bayesian network using information from at least one reliability model of the technical system, creating parameters of the Bayesian network using information from the reliability model of the technical system, the Bayesian network model having a plurality of observation nodes, obtaining information about the plurality of observation nodes from a list of observations that augments information contained in the reliability model of the technical system, and inserting the observation nodes into the created structure of the Bayesian network.