Driving Technologies for the Design of Additive Manufacturing Systems

The Additive Manufacturing (AM) technology, belonging to the most comprehensive Net Shape Forming family, has in recent years a growing trend due to the increasing quality of the built product. These results may open the application of the AM to the industrial field, moving the application from laboratories to the plant floor. This step requires machines capable of executing the technology process of AM with the requirements of the industrial environment, concerning as example the production speed, reliability, robustness, and process stability. The design of such type of machinery requires a systematic and multidisciplinary approach for reaching these industrial targets. Indeed the AM process involves several design technological issues, like temperature control of the material to be processed, characteristics of the energy source for material transition, control of the power transferred to the material, scanning system’s head control, 3D model’s layer definition, generation of the laser point’s trajectories. The final product’s quality strongly depends on all these aspects synergically linked each other, as well as on the technical solutions to realize them. The paper presents an interdisciplinary approach to the design of machines for AM, based on the Powder Bed Fusion process, and targeted to the industrial field. The technological platforms discussed in the paper are essential for such type of machines. The strategy proposed constitutes a base reference point for the definition of a methodological approach to the design of AM machinery. Doi: 10.28991/HIJ-2021-02-01-03 Full Text: PDF

Merging Agents and Cloud Services in Industrial Applications

A novel idea to combine agent technology and cloud computing for monitoring a plant floor system is presented. Cloud infrastructure has been leveraged as the main mechanism for hosting the data and processing needs of a modern industrial information system. The cloud offers unlimited storage and data processing in a near real-time fashion. This paper presents a software-as-a-service (SaaS) architecture for augmenting industrial plant-floor reporting capabilities. This reporting capability has been architected using networked agents, worker roles, and scripts for building a scalable data pipeline and analytics system.

The Costs of Downtime Incidents in Serial Multistage Manufacturing Systems

Downtime is arguably the single most significant contributor to system inefficiency in a multistage manufacturing system. Achieving near-zero downtime has been the ultimate goal of production operation management at the plant floor. Accurate estimation of the impact of each downtime incident is of great importance for deciding where to allocate limited resources among various manufacturing stages. In this paper, we focus on quantitative analysis of the impact of each individual downtime event in terms of permanent production loss and financial cost. We start from the transient analysis of a single downtime event and later extend to more generic scenarios where downtime incidents occur concurrently at different stages. Apart from the analytical study, a practical computation procedure using real-time production records can be readily derived and implemented at the plant floor. Case studies are conducted to demonstrate its potential in facilitating the decision making at plant floor on project identification, prioritization, and budget allocation in a multistage manufacturing system.