TCO evaluation in physical asset management : benefits and limitations for industrial adoption

Part 1: Knowledge-Based Performance ImprovementInternational audienceNowadays, the evaluation of the total cost of ownership (TCO) of an asset for supporting informed decision-making both for investments and managerial issues within the asset management framework is gaining increasing attention in industry. Nevertheless its application in practice is still limited. The aim of this paper is to analyze the benefits and limitations of the adoption of TCO evaluation in asset management. Based on a literature review, the paper defines a framework that categorizes the benefits and potential applications that a TCO model can have for different stakeholders. Together with that, industry related issues that influence its implementation are also considered. Finally, empirical evidences are analyzed through a multiple case study to understand if those benefits are recognized in practice and which are the limitations for the practical adoption of a TCO model that should allow exploiting such benefits

Monitoring of Collaborative Assembly Operations: An OEE Based Approach

International audienceIn this paper we present requirements and concept generation principles for performance monitoring of a collaborative assembly task. Life cycle aspects are considered and an Overall Equipment Efficiency (OEE) based monitoring scenario for a developed passive collaborative robot (COBOT) test system is presented. In this case main benefits of applying COBOT are expected to be: improved productivity, improved quality, reduced production cost and improved ergonomics. Since human and COBOT are working co-operatively human actions have also affects on process performance, i.e. OEE. However a human's and machines or a COBOT's efficiency are undistinguishable directly from OEE factors. It is possible to infer cause of lower efficiency from the variables from which OEE factors are calculated. One such variable is cycle time, which is used to define performance efficiency

Magnetic microrheometry of tumor-relevant stiffness levels and probabilistic quantification of viscoelasticity differences inside 3D cell culture matrices.

The progression of breast cancer involves cancer-cell invasions of extracellular matrices. To investigate the progression, 3D cell cultures are widely used along with different types of matrices. Currently, the matrices are often characterized using parallel-plate rheometry for matrix viscoelasticity, or liquid-like viscous and stiffness-related elastic characteristics. The characterization reveals averaged information and sample-to-sample variation, yet, it neglects internal heterogeneity within matrices, experienced by cancer cells in 3D culture. Techniques using optical tweezers and magnetic microrheometry have measured heterogeneity in viscoelasticity in 3D culture. However, there is a lack of probabilistic heterogeneity quantification and cell-size-relevant, microscale-viscoelasticity measurements at breast-tumor tissue stiffness up to ≃10 kPa in Young's modulus. Here, we have advanced methods, for the purpose, which use a magnetic microrheometer that applies forces on magnetic spheres within matrices, and detects the spheres displacements. We present probabilistic heterogeneity quantification using microscale-viscoelasticity measurements in 3D culture matrices at breast-tumor-relevant stiffness levels. Bayesian multilevel modeling was employed to distinguish heterogeneity in viscoelasticity from the effects of experimental design and measurement errors. We report about the heterogeneity of breast-tumor-relevant agarose, GrowDex, GrowDex-collagen and fibrin matrices. The degree of heterogeneity differs for stiffness, and phase angle (i.e. ratio between viscous and elastic characteristics). Concerning stiffness, agarose and GrowDex show the lowest and highest heterogeneity, respectively. Concerning phase angle, fibrin and GrowDex-collagen present the lowest and the highest heterogeneity, respectively. While this heterogeneity information involves softer matrices, probed by ≃30 μm magnetic spheres, we employ larger ≃100 μm spheres to increase magnetic forces and acquire a sufficient displacement signal-to-noise ratio in stiffer matrices. Thus, we show pointwise microscale viscoelasticity measurements within agarose matrices up to Young's moduli of 10 kPa. These results establish methods that combine magnetic microrheometry and Bayesian multilevel modeling for enhanced heterogeneity analysis within 3D culture matrices

Improving Components Feeding: A Rotatory Device

Packaging lines need to create small batches of components before the \ufb01nal kitting operation. This task is usually performed by mechanical hoppers that require a certain amount of time to be ready for the next loading operation. In this paper, a new device that reduces this amount of time is proposed. Such device is composed of a single rotational part whose shape is optimized to help components falling with a free falling motion, minimizing the takt time of the device. The blades of the device are designed with a proper algorithm that consider the composition of motion of the impeller and of the components

Evaluation of time-gated Raman spectroscopy for the determination of nitric, sulfuric and hydrofluoric acid concentrations in pickle liquor

Abstract The focus of this study was to assess the feasibility of time-gated Raman spectroscopy for stainless steel pickle liquor acid quantification. Pickle liquor is used for dissolving metal surface impurities during the pickling process. The pickle liquor samples consisted mainly of 11–89 g/L HNO₃, 20–160 g/L H₂SO₄, 5–57 g/L HF and stainless steel residue. Raman peaks correlating with the different acids were identified in both aqueous and pickle liquor solutions. The linearity between Raman scattering intensity and acid concentration was studied. Multivariate PLSR calibration for pickle liquor HNO₃, H₂SO₄ and HF quantification was also investigated. Time-gated Raman spectroscopy was found to be a promising technique for pickle liquor HNO₃ and H₂SO₄ quantification

Cooperative colloidal self-assembly of metal-protein superlattice wires

Material properties depend critically on the packing and order of constituent units throughout length scales. Beyond classically explored molecular self-assembly, structure formation in the nanoparticle and colloidal length scales have recently been actively explored for new functions. Structure of colloidal assemblies depends strongly on the assembly process, and higher structural control can be reliably achieved only if the process is deterministic. Here we show that self-assembly of cationic spherical metal nanoparticles and anionic rod-like viruses yields well-defined binary superlattice wires. The superlattice structures are explained by a cooperative assembly pathway that proceeds in a zipper-like manner after nucleation. Curiously, the formed superstructure shows right-handed helical twisting due to the right-handed structure of the virus. This leads to structure-dependent chiral plasmonic function of the material. The work highlights the importance of well-defined colloidal units when pursuing unforeseen and complex assemblies.Peer reviewe

Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators

Abstract Background: Cognitive load (CL) management is essential in safety-critical fields so that professionals can monitor and control their cognitive resources efficiently to perform and solve scenarios in a timely and safe manner, even in complex and unexpected circumstances. Thus, cognitive load theory (CLT) can be used to design virtual reality (VR) training programmes for professional learning in these fields. Objectives: We studied CL management performance through behavioural indicators in authentic VR flight training and explored if and to what extent physiological data was associated with CL management performance. Methods: The expert (n = 8) and novice pilots (n = 6) performed three approach and landing scenarios with increasing element interactivity. We used video recordings of the training to assess CL management performance based on the behavioural indicators. Then, we used the heart rate (HR) and heart rate variability (HRV) data to study the associations between the physiological data and CL management performance. Results and Conclusions: The pilots performed effectively in CL management. The experience of the pilots did not remarkably explain the variation in CL management performance. The scenario with the highest element interactivity and an increase in the very low-frequency band of HRV were associated with decreased performance in CL management. Takeaways: Our study sheds light on the association between physiological indicators and CL management performance, which has traditionally been assessed with behavioural indicators in professional learning in safety-critical fields. Thus, physiological measurements can be used to supplement the assessment of CL management performance, as relying solely on behavioural indicators can be time consuming