An OSGi-based production process monitoring system for SMEs

The present paper proposes an architecture for a product process monitoring system suitable for SMEs (Small-Medium Enterprises). The monitoring system is the main means by which decision-making systems based on intelligent automation technologies are aware of the state of the system on which they will take decisions. Methods and tools from best-practice and best-effort approaches are proposed in the context of SMEs, where the requirements of low cost, low initial level of digitisation and high production flexibility often coexist and contribute to the complexity of management and control problems in these companies. The paper focuses on the design of the monitoring system using an OSGi framework to meet industry standards and Industry 4.0 requirements, taking into account the peculiarities of SMEs as design constraints. The proposed architecture was first tested using a simulation tool and then implemented on a full-scale production line used for data collection

The KIMORE dataset: KInematic assessment of MOvement and clinical scores for remote monitoring of physical REhabilitation

The paper proposes a free dataset, available at the following link1, named KIMORE, regarding different rehabilitation exercises collected by a RGB-D sensor. Three data inputs including RGB, Depth videos and skeleton joint positions were recorded during five physical exercises, specific for low back pain and accurately selected by physicians. For each exercise, the dataset also provides a set of features, specifically defined by the physicians, and relevant to describe its scope. These features, validated with respect to a stereophotogrammetric system, can be analyzed to compute a score for the subject's performance. The dataset also contains an evaluation of the same performance provided by the clinicians, through a clinical questionnaire. The impact of KIMORE has been analyzed by comparing the output obtained by an example of rule and template-based approaches and the clinical score. The dataset presented is intended to be used as a benchmark for human movement assessment in a rehabilitation scenario in order to test the effectiveness and the reliability of different computational approaches. Unlike other existing datasets, the KIMORE merges a large heterogeneous population of 78 subjects, divided into 2 groups with 44 healthy subjects and 34 with motor dysfunctions. It provides the most clinically-relevant features and the clinical score for each exercise

Fault Detection and Isolation of Linear Discrete-Time Periodic Systems Using the Geometric Approach

This paper solves the problem to detect and isolate faults in linear periodic discrete-time systems. A residual generator is designed through a suitable unknown input observer with the requirement that each residual should be sensitive only to one fault and, simultaneously, insensitive to the other faults that can affect the system, and with the additional requirement of -detectability, that is the transition matrix of its relative error system has all eigenvalues smaller than , in modulus, for a given positive 1. The solution is based on geometric tools, and it makes use of the outer observable subspace notion

Il capitale umano nel paradigma dell'Industria 4.0

Il nuovo paradigma Industria 4.0, ovvero della quarta rivoluzione industriale, mira ad una produzione del tutto automatizzata ed interconnessa presentando, in apparenza, rischi di riduzione degli occupati nei processi produttivi, ma di fatto, capace di produrre notevoli opportunità di sviluppo. Industria 4.0 porta con sé nuove sfide e notevoli cambiamenti all’intero ciclo di vita del processo produttivo, tale da non poter prescindere da una profonda evoluzione in termini di conoscenze e competenze da parte della classe imprenditoriale ma anche da parte dell’intero capitale umano su cui il sistema industriale può contare. Le linee guida sviluppate dal Ministero dello Sviluppo Economico nel Piano nazionale Industria 4.0 si basano su nuovi modelli di governance e su modelli organizzativi ed innovativi, che mirano alla costituzione di un sistema culturale nuovo, attraverso il rafforzamento delle competenze digitali esistenti e introducendo direttrici tecnologiche completamente innovative. Il contributo mira a fornire una panoramica delle opportunità che questo scenario può offrire in termini delle conoscenze e competenze utili ad accrescere il valore del capitale mano nei diversi settori produttivi

Fault Detection for Linear Periodic Systems Using a Geometric Approach

Using the geometric approach, a solution is given to the problem of detecting faults in linear periodic discrete-time systems. The solution consists on developing an unknown input observer. The existing conditions are provided in terms of new geometric notion of outer observable subspace that is the dual notion of inner reachable subspace. Making use of the new notion, a residual generator is developed, such that the residual is made independent of unknown input disturbance, and its output-free response goes asymptotically to zero

Quegli artisti che chiamiamo insegnanti

In una società che incontenibilmente si trasforma, la conoscenza, la ricerca e la sua valorizzazione, possono aiutarci sia a decifrare che a scoprire ciò che ci circonda. In tutto questo l’insegnante ha un ruolo fondamentale, da riscoprire e riabilitare. L’insegnante è come un artista a cui è affidato il compito di lasciare un segno e di leggere la complessità degli eventi, oggi più che mai. È lui che potrà accompagnarci verso la conoscenza e traghettarci verso il futuro

A coordination architecture for UUV fleets

This paper presents a modular and expandable architecture, which includes diversified functions and can be applied to heterogeneous fleets of unmanned underwater vehicles (UUVs), to solve the problem of decentralized formation coordination. The architecture is modular and each module is built such that it can solve a precise task using one or more functions. Three functions among them play a key role for the whole architecture: localization, faultless formation control and fault tolerance. The localization function is performed by the use of an adaptive extended Kalman filter (A-EKF) algorithm; the fault-free formation control function is based on a nonlinear decentralized model predictive control (ND-MPC) algorithm; the fault tolerance function is based on a hierarchy graph theory. The novelty of the paper lies in the use of the above mentioned functions as the core of an architecture which is expandable, decentralized and can be applied to a wide range of vehicles

A detection-estimation approach to filtering with intermittent observations with generally correlated packet dropouts

This paper is concerned with the problem of state estimation for the class of linear discrete-time Gaussian systems with intermittent observations due to packet losses. This is a common case in networked control systems, where the state of a remote plant is estimated from measurements carried through a lossy network. We assume that the receiver does not know the sequence of packet dropouts. This is typical, e.g., in wireless sensor networks or in networks that cannot rely on protocols that provide information on packet loss. Moreover, we assume that the sequence of packet dropouts is correlated, thus subsuming both the cases of independent dropouts and dropouts modeled as a Markov chain. We propose a detection-estimation approach to the problem of state estimation. The estimator consists of two stages: the first is a nonlinear optimal detector, which decides if a packet dropout has occurred, and the second is a time-varying Kalman filter, which is fed with both the observations and the decisions from the first stage. The overall estimator has finite memory and the tradeoff between performance and computational complexity can be easily controlled. As a case study, we derive the decision rule in closed form in the case of dropout sequence modeled as a Markov chain. Simulation results highlight the effectiveness of the proposed approach, which outperforms the linear recursive estimator of Hadidi and Schwartz