The way machining operations have been running has changed over the years. Nowadays, machine utilization and availability monitoring are becoming increasingly important for the smooth operation of modern workshops. Moreover, the nature of jobs undertaken by manufacturing small and medium enterprises (SMEs) has shifted from a mass production to small batch. To address the challenges caused by modern fast changing environments, a new cloud-based approach for monitoring the use of manufacturing equipment, dispatching jobs to the selected computer numerical control (CNC) machines, and creating the optimum machining code is presented. In this approach the manufacturing equipment is monitored using a sensor network and though an information fusion technique it derives and broadcasts the data of available tools and machines through the internet to a cloud-based platform. On the manufacturing equipment event driven function blocks with embedded optimization algorithms are responsible for selecting the optimal cutting parameters and generating the moves required for machining the parts while considering the latest information regarding the available machines and cutting tools. A case study based on scenario from a shop floor that undertakes machining jobs is used to demonstrate the developed methods and tools.

Power skiving is a new machining process that allows the manufacturing of external and internal gears while achieving high throughputs. Although the process was first described during the nineteenth century, it is not until lately that advances in machine tool technology allowed for the process to be implemented on an industrial scale. This paper presents a novel simulation model that enables the accurate prediction of the non-deformed chip geometry, the form and dimensions of the chips produced during the cutting process as well as the characteristics of the gear gap. The simulation model is embedded on a CAD environment in order to take advantage of their increased accuracy. Through the simulation code, the virtual simulation of the manufacturing process is realised. The simulation model was verified with the use of analytical equations regarding the form of the gear. Chip geometry and dimensions for internal and external gears machined with different conditions are also presented.

In many machining operations, metalworking fluids (MWFs) play an invaluable role. Often, proper application of an intelligent MWF strategy allows manufacturing processes to benefit from a multitude of operational incentives, not least of which are increased tool life, improved surface integrity and optimised chip handling. Despite these clearly positive implications, current MWF strategies are often unable to accommodate the environmental, economic and social conscience of industrial environments. In response to these challenges, CO₂ coolants are postulated as an operationally viable, environmentally benign MWF solution. Given the strong mechanistic rationale and historical evidence in support of cryogenic coolants, this review considers the technological chronology of cryogenic MWF’s in addition to the current state-of-the-art approaches. The review also focuses on the use of CO₂ coolants in the context of the machining of a multitude of material types in various machining conditions. In doing so, cryogenic assisted machining is shown to offer a litany of performance benefits for both conventional emulsion (flood) cooling and near dry strategies, i.e., minimum quantity lubrication (MQL), as well as aerosol dry lubrication (ADL).

Through the Internet of Things (IoT) interaction between objects becomes possible in a way we have never seen before. With the advent of IoT and its introduction into almost all aspects of life, safety and security of IoT devices has to be considered for their whole life cycle. This concerns not only the large amounts of data that needs to be exchanged securely but also the design of the hardware of the devices themselves. Security has to be designed right from the start into IoT devices rather than added on later. This paper will introduce a global strategy for secure Design for IoT which includes: • Safe solutions for environments with rich information • Guarantee that the devices are functioning as intended by the manufacturer and are not damaged • Life cycle security across devices, networks and data centers • Support for industry standards and interoperability of devices • Ability to solve the challenges of the information link • Secure Clouds for traditional systems. This paper lays the foundation for the creation of a safe remote monitoring system for machine tools through IoT devices and analyses the critical issues focusing on the manufacturing environment