Selective laser melting: Evaluation of the effectiveness and reliability of multi-scale multiphysics simulation environments.

This study evaluates the effectiveness and reliability of Multi-scale Multiphysics Selective Laser Melting (SLM) Simulation Environments. A literature review and bibliometric analysis were conducted to identify the most widely used SLM Simulation Environments. The effectiveness of simulation environments was assessed through a SWOT analysis enhanced by an Analytic Network Process (ANP). The reliability of simulation environments was analysed through a design of experiment (DoE). The DoE solely assessed the ability of these environments to accurately predict part distortion. The results showed that the most robust SLM process simulation modelling systems are Ansys Additive Print, Comsol, Simufact Additive, Netfabb, and Simulia.

Development of a framework for improving the turnaround time of the application process at the South African Civil Aviation Authority.

Drones are considered to become more significant as technology develops and be used in creative ways. The aim of this paper is to develop a framework to improve the turnaround time (TAT) of the drone application process at South African Civil Aviation Authority (SACAA). According to some of the drone companies, application process of drone approval takes time to complete. These delays impact negatively to drone companies in South Africa. Drone operators were interviewed, and the current status of the application process was captured. Thirteen drone operators were interviewed using a structured set of questionnaires. Results show that application process is not well implemented and that the structure does not create a positive outcome to the South African drone industry. Findings indicate that the average turnaround time to complete the approval process is long, and it is time consuming. The framework to improve the current turnaround time of the application process was developed. The proposed framework consists of three techniques (process activities improvement, capacity enhancement and process redesign). The proposed framework can be used as a guide to improve the situation at SACAA. .

Analysis of potential materials for local production of a rail car component using additive manufacturing.

In the rail industry, unavailability of spare parts can have negative implications such as downtime and financial losses. Long lead times can be experienced in the process of replacing a damaged spare part. Some of the parts are expensive to produce in-house using conventional methods because of the tooling costs. It can be time consuming to wait for suppliers to replace the part if it is not produced locally. Proper maintenance of vehicles requires spare parts to be available timeously. It is necessary to investigate how parts can be produced using locally available technologies and materials. The aim of this study is to analyse potential materials that can be used to produce a rail car component. The use of Additive Manufacturing (AM) to produce parts on demand is a quicker and flexible approach when compared to conventional manufacturing methods. Taking advantage of the flexibility offered by the AM, three alternative high performance materials are considered to reduce the weight, improve functional performance and service life of the part. The performance of all the three materials are tested and analysed using Finite Element Analysis. The results of this study are useful in providing guidance on the development of a suitable process chain for producing the part locally. This demonstrates the capability of AM as a suitable approach for enabling local sustainable production of spare parts for the rail industry.

Application of lean Six Sigma methodology using DMAIC approach for the improvement of bogie assembly process in the railcar industry.

The quest for waste reduction, quality improvement and operational efficiency during the assembly process of the railcar bogie necessitates this study. Using a case study approach, this study employs the Lean Six Sigma (LSS) approach for process improvement of the railcar bogie assembly process. Primary data relating to the assembly process such as the labour and material flow, up and down times were collected at every stage of the assembly operation. The improvement process of the assembly process featured the use of some Lean tools such as the Kaizen, Value Stream Mapping, Pareto chart, Single-Minute Exchange of Die (SMED) and 5S. The investigation of the current assembly process with the use of the LSS technique indicates that the process efficiency is low due to waste generation. The results obtained showed significant improvement in the process cycle efficiency (PCE) by 46.8%, via the implementation of the Kaizen continuous process improvement approach, 27.9% reduction in the lead-time, 59.3% increase in the value added time and 71.9% reduction in the non-value added time after the implementation of the LSS approach. The findings of this work demonstrated the feasibility of the LSS approach for waste minimisation and process performance improvement in a bid to achieve operational excellence in a manufacturing organisation.

Review of life cycle models for enhancing machine tools sustainability: lessons, trends and future directions.

The life cycle models are critical in the assessment of the performance of a product from the design phase to its end of life (EoL). With the quest for manufacturing sustainability with respect to energy, process, material, and environment friendliness as well as the clamour for circular economy which emphasizes zero tolerance for waste, there is a need for a critical review of the life cycle of machine tool employed for machining operations and product development. The objective of this study is to evaluate the efficient way of managing the machine tools throughout its lifecycle. Several studies have been conducted in analysing the life cycle of the machine tools and different strategies were employed for its design, manufacture, use, maintenance and recovery at the end of life. The common approach to ensure environmental sustainability was established when comparing the literature studied. From the articles reviewed 60% applied life cycle assessment (LCA) methodology to reduce energy consumption and enhance environmental sustainability, while 40% employed other assessment tools. In this study an integrated life cycle and cyber physical machine tool model is proposed.

Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept.

In this article, a novel hybridized Multi-Attribute Decision Model (MADM) is developed to identify an optimal design of a Reconfigurable Assembly Fixture (RAF) from a set of alternative design concepts. The model combines the comparative advantage of Fuzzy Analytic Hierarchy Process (FAHP) and the computational strength of the Fuzzy Weighted Average (FWA) based on left and right scores in order to obtain aggregates for the design alternatives considering the relative importance of the design criteria as needed in the optimal design. The model was applied to evaluate four design concepts of a RAF with six design features having numerous sub-features. Results obtained from the evaluation process shows that there are differences in final values of the design alternatives. However, a close variation exists between these values. These differences can be accrued to the interrelationships between the design features and sub-features obtained from the Fuzzy Synthetic Extent (FSE) of the FAHP and an unambiguity judgment of the FWA when aggregating availability of the design features and sub-features in the design alternatives.