Titanium and nickel alloys are the most commonly used in the demanding industries like aerospace, energy, petrochemical, and biomedical. These highly engineered alloys offer unique combination of heat resistance, corrosion resistance, toughness, high operating temperature, and strength-to-weight ratio. These alloys are termed as “Difficult to cut materials” because of their low machinability rating. They are difficult to machine because of properties like low thermal conductivity, high strength at elevated temperatures, and high chemical reactivity. Machining of titanium- and nickel-based alloys causes problems of surface integrity and selection of cutting tool materials that is always a challenge for manufacturers. In this work, machinability studies for titanium and nickel alloys are reviewed with reference to cutting tool materials, associated wear mechanisms, failure modes, and novel tooling techniques. It also discusses major surface integrity defects like carbide cracking, white layer formation, work hardening layer formation, residual stresses, and microstructural alterations. Major aim of this work is to evaluate the challenges involved in improving machinability of the titanium- and nickel-based alloys, and determine the future research direction for productivity improvements in machining these alloys.

The recent circular economy movement has raised awareness and interest about untapped environmental and economic potential in the manufacturing industry. One of the crucial aspects in the implementation of circular or closed-loop manufacturing approach is the design of circular products. While it is obvious that three post-use strategies, i.e., reuse, remanufacturing, and recycling, are highly relevant to achieve loop closure, it is enormously challenging to choose “the right” strategy (if at all) during the early design stage and especially at the single component level. One reason is that economic and environmental impacts of adapting these strategies are not explicit as they vary depending on the chosen business model and associated supply chains. In this scenario, decision support is essential to motivate adaptation of regenerative design strategies. The main purpose of this paper is to provide reliable decision support at the intersection of multiple lifecycle design and business models in the circular economy context to identify effects on cost and CO₂ emissions. The development of this work consists of a systematic method to quantify design effort for different circular design options through a multi-method simulation approach. The simulation model combines an agent-based product architecture and a discrete event closed-loop supply chain model. Feasibility of the model is tested using a case of a washing machine provided by Gorenje d.d. Firstly, design efforts for reuse, remanufacturing, and recycling are quantified. Secondly, cost and emissions of different design options are explored with different business model configurations. Finally, an optimization experiment is run to identify the most cost-effective combination of reused, remanufactured, and recycled components for a business model chosen on the basis of the explorative study results.

This paper introduces an agent-based approach to study customer behavior in terms of their acceptance of new business models in Circular Economy (CE) context. In a CE customers are perceived as integral part of the business and therefore customer acceptance of new business models becomes crucial as it determines the successful implementation of CE. However, tools or methods are missing to capture customer behavior to assess how customers will react if an organization introduces a new business model such as leasing or functional sales. The purpose of this research is to bring forward a quantitative analysis tool for identifying proper marketing and pricing strategies to obtain best fit demand behavior for the chosen new business model. This tool will support decision makers in determining the impact of introducing new (circular) business models. The model has been developed using an agent-based modeling approach which delivers results based on socio-demographic factors of a population and customers’ relative preferences of product attributes price, environmental friendliness and service-orientation. The implementation of the model has been tested using the practical business example of a washing machine. This research presents the first agent-based tool that can assess customer behavior and determine whether introduction of new business models will be accepted or not and how customer acceptance can be influenced to accelerate CE implementation. The tool integrates socio-demographic factors, product utility functions, social network structures and inter-agent communication in order to comprehensively describe behavior on individual customer level. In addition to the tool itself the results of this research indicates the need for systematic marketing strategies which emphasize CE value propositions in order to accelerate customer acceptance and shorten the transition time from linear to circular. Agent-based models are emphasized as highly capable to fill the gap between diffusion-based penetration of information and resulting behavior in the form of purchase decisions.

Additive manufacturing (AM) has recently been accorded considerable interest by manufacturers. Many manufacturing industries, amongst others in the aerospace sector, are already using AM parts or are investing in such manufacturing methods. Important material properties, such as microstructures, residual stress, and surface topography, can be affected by AM processes. In addition, a subtractive manufacturing (SM) process, such as machining, is required for finishing certain parts when accurate tolerances are required. This finish machining will subsequently affect the surface integrity and topography of the material. In this research work, we focused on the surface integrity of Ti-6Al-4V parts manufactured using three different types of AM and finished using an SM step. The aim of this study was to gain an understanding on how each process affects the resulting surface integrity of the material. It was found that each AM process affects the materials’ properties differently and that clear differences exist compared to a reference material manufactured using conventional methods. The newly generated surface was investigated after the SM step and each combination of AM/SM resulted in differences in surface integrity. It was found that different AM processes result in different microstructures which in turn affect surface integrity after the SM process.