Industrial dimensional assessment presents instances in which early control is exerted among “warm” (approx. 600 ${}^{\circ }$C) pieces. Early control saves resources, as defective processes are timely stopped and corrected. Existing literature is devoid of dimensional assessment on warm workpieces. In response to this absence, this manuscript presents the implementation and results of an optical system which performs in-line dimensional inspection of revolution warm workpieces singled out from the (forming) process. Our system can automatically measure, in less than 60 s, the circular runout of warm revolution workpieces. Such a delay would be 20 times longer if cool-downs were required. Off-line comparison of the runout of T-temperature workpieces (27 ${}^{\circ }$C ≤ T ≤ 560 ${}^{\circ }$C) shows a maximum difference of 0.1 mm with respect to standard CMM (Coordinate Measurement Machine) runout of cold workpieces (27 ${}^{\circ }$C), for workpieces as long as 160 mm. Such a difference is acceptable for the forging process in which the system is deployed. The test results show no correlation between the temperature and the runout of the workpiece at such level of uncertainty. A prior-to-operation Analysis of Variance (ANOVA) test validates the repeatability and reproducibility (R&R) of our measurement system. In-line assessment of warm workpieces fills a gap in manufacturing processes where early detection of dimensional misfits compensates for the precision loss of the vision system. The integrated in-line system reduces the number of defective workpieces by $95\%$ .

In the context of computer numeric control (CNC)-based sheet metal laser cutting, the problem of heat transfer simulation is relevant for the optimization of CNC programs. Current physically based simulation tools use numeric or analytic algorithms which provide accurate but slow solutions due to the underlying mathematical description of the model. This paper presents: (1) an analytic solution to the laser heating problem of rectangular sheet metal for curved laser trajectories and convective cooling, (2) a graphics processing unit (GPU) implementation of the analytic solution for fast simulation of the problem, and (3) an integration within an interactive environment for the simulation of sheet metal CNC laser cutting. This analytic approach sacrifices the material removal effect of the laser cut in the favor of an approximated real-time temperature map on the sheet metal. The articulation of thermal, geometric, and graphic feedback in virtual manufacturing environments enables interactive redefinition of the CNC programs for better product quality, lower safety risks, material waste, and energy usage among others. The error with respect to finite element analysis (FEA) in temperature prediction descends as low as 3.5%.

Interactive multi-beam laser machining simulation is crucial in the context of tool path planning and optimization of laser machining parameters. Current simulation approaches for heat transfer analysis (1) rely on numerical Finite Element methods (or any of its variants), non-suitable for interactive applications; and (2) require the multiple laser beams to be completely synchronized in trajectories, parameters and time frames. To overcome this limitation, this manuscript presents an algorithm for interactive simulation of the transient temperature field on the sheet metal. Contrary to standard numerical methods, our algorithm is based on an analytic solution in the frequency domain, allowing arbitrary time/space discretizations without loss of precision and non-monotonic retrieval of the temperature history. In addition, the method allows complete asynchronous laser beams with independent trajectories, parameters and time frames. Our implementation in a GPU device allows simulations at interactive rates even for a large amount of simultaneous laser beams. The presented method is already integrated into an interactive simulation environment for sheet cutting. Ongoing work addresses thermal stress coupling and laser ablation.

In the context of smart manufacturing, the concept of Visual Computing is a key enabling technology for Industry 4.0. Visual Computing and Physically-based simulation enables the implementation of interactive, visual and (in most cases) non-disruptive solutions within the context of (a) the production process (off-line or in-line) the shop floor, (b) the interaction with customers and clients in the whole value chain, and/or (c) the product-service schemas. Technologies such as Industrial Big Data, Human-Robot Collaboration, IIOT & 5G, Cybersecurity, Cyber-Physical Systems, Semantic Technologies, Visual Computing and other related technologies have a strong impact in the new ways smart manufacturing is reconfiguring the production. This article presents a theoretical framework for the incorporation of Visual Computing and Physically-based Simulation technologies to Industry 4.0 and Operator 4.0 scenarios. This framework has been already implemented and supports different smart manufacturing scenarios, already running in many SME. Three practical study case scenarios (already deployed into SMEs) are presented and discussed.