A specific method for the life cycle inventory of machine tools and its demonstration with two manufacturing case studies

Zendoia, Jose; Woy, Udisien; Ridgway, Nicola; Pajula, Tiina; Unamuno, Gorka; Olaizola, Aratz; Fysikopoulos, Apostolos; Krain, Roland

doi:10.1016/j.jclepro.2014.05.012

Cited by 21 publications

(18 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Over the years, practitioners have addressed this lack of LCI data through strategies such as a methodology to collect data in a manufacturing process (Zendoia et al 2014) and a proposal to use substitute or proxy datasets of existing processes to deal with the lack of data (Subramanian and Golden 2016). A strategy to determine LCI data of unconventional machining processes has also been proposed by (Gamage et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Bridging LCA data gaps by use of process simulation for energy generation

Morales-Mendoza

Azzaro‐Pantel

2017

Clean Techn Environ Policy

View full text Add to dashboard Cite

Life Cycle Assessment (LCA) is now a mature environmental management strategy that is internationally standardized. A cornerstone of LCA involves Life Cycle Inventory (LCI) databases, which are largely implemented in several types of research. Finding consistent and transparent LCI data for LCAs still remains difficult. Setting up inventory data can be one of the most labour-and timeintensive stages of LCA. It is often challenging due to the lack of appropriate data for the product system under study (e.g. for production of chemicals). With the aim of bridging this gap, this paper proposes the combined use of a process simulation tool, experimental process data and LCA for the computation of energy-related emissions in connection with a given process. The case studies address the environmental impact assessment associated with steam production from a gas turbine. The practical application of the methodological framework is that different operating conditions and technologies can be modelled and evaluated systematically by an energy production simulator, in order to mitigate the effect of lack of data on environmental impact assessments. The combination of LCA and process modelling enables various alternatives for the energy production process to be assessed and can thus be used as a support for decision-making in a system-based approach.

show abstract

Section: Introductionmentioning

confidence: 99%

Bridging LCA data gaps by use of process simulation for energy generation

Morales-Mendoza

Azzaro‐Pantel

2017

Clean Techn Environ Policy

View full text Add to dashboard Cite

show abstract

“…Duflou et al (2012) highlights the machine tools as tools necessary for imparting the desired shape in a material in order to meet the geometrical and dimensional requirements of the final product on a specified structure. The impact of the machine tools on the environment is considered as the most critical factor during the use phase of a Life Cycle Assessment (LCA), because machine tools induces energy during operation (Santos et al, 2011;Hu et al, 2012;Akbari et al, 2001;Zein et al, 2011;Zendoia et al, 2014;Vijayaraghavan and Dornfeld 2010;Azevedo et al, 2011;Azkarate et al, 2011;Zhou et al, 2016;Hwang et al, 2009;Geissdoerfer et al, 2017). According to Diaz et al (2010) activities in the manufacturing industry accounts for 19% of the world's greenhouse gas emissions.…”

Section: Introductionmentioning

confidence: 99%

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

Daniyan

Mpofu

Ramatsetse

et al. 2021

Heliyon

View full text Add to dashboard Cite

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.

show abstract

“…Todays' manufacturing era focuses on monitoring the process on shop-floor by utilizing various sensorial systems that are based on data collection [1][2][3]. The automated systems directly collect an enormous amount of performance data from the shop-floor ( Figure 1), and are stored into a repository, in a raw or accumulated form [4,5]. However, automated decision making in the era of Industry 4.0 is yet to be discovered.…”

Section: Introductionmentioning

confidence: 99%

A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT

Papacharalampopoulos,

Giannoulis,

Stavropoulos

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

A dashboard application is proposed and developed to act as a Digital Twin that would indicate the Measured Value to be held accountable for any future failures. The current study describes a method for the exploitation of historical data that are related to production performance and aggregated from IoT, to eliciting the future behavior of the production, while indicating the measured values that are responsible for negative production performance, without training. The dashboard is implemented in the Java programming language, while information is stored into a Database that is aggregated by an Online Analytical Processing (OLAP) server. This achieves easy Key Performance Indicators (KPIs) visualization through the dashboard. Finally, indicative cases of a simulated transfer line are presented and numerical examples are given for validation and demonstration purposes. The need for human intervention is pointed out.

show abstract

A specific method for the life cycle inventory of machine tools and its demonstration with two manufacturing case studies

Cited by 21 publications

References 15 publications

Bridging LCA data gaps by use of process simulation for energy generation

Bridging LCA data gaps by use of process simulation for energy generation

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

A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT

Contact Info

Product

Resources

About