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Bonilla Hernández, Ana EstherORCID iD iconorcid.org/0000-0002-2146-7916
Publications (8 of 8) Show all publications
Bonilla Hernández, A. E. (2019). On how the selection of materials affects sustainability. Paper presented at Conference of 16th Global Conference on Sustainable Manufacturing, GCSM 2018 ; Conference Date: 2 October 2018 Through 4 October 2018. Procedia Manufacturing, 33, 625-631
Open this publication in new window or tab >>On how the selection of materials affects sustainability
2019 (English)In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 33, p. 625-631Article in journal (Refereed) Published
Abstract [en]

The selection of the materials for the production of aerospace engine products is directly related to their performance in tough working conditions. However, the extraction of the materials requires high amounts of energy, use water and emit CO2, which can be directly related with environmental sustainability. The abundance of the materials and their sourcing and geographical location can be further related to economic and social sustainability. Manufacturing companies look for different materials and cutting data that will optimize material removal rate, cutting tool utilization, required cutting time, costs, energy used, CO2 footprint, coolants, etc. Here is presented a simple methodology to calculate the sustainability impact of the selection of materials. The study compares a simplified theoretical work piece that is geometrically complex and made of difficult to machine material, e.g. Ti-6Al-4V and MP159. The study shows how to select the optimal material, not only in terms of costs, but also in terms of environmental, societal and economical sustainability. © 2019 The Authors. Published by Elsevier B.V.

Keywords
End of Life, Machining process, Sustainability, Triple Bottom Line
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology; ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-14466 (URN)10.1016/j.promfg.2019.04.078 (DOI)2-s2.0-85068581084 (Scopus ID)
Conference
Conference of 16th Global Conference on Sustainable Manufacturing, GCSM 2018 ; Conference Date: 2 October 2018 Through 4 October 2018
Funder
Knowledge Foundation
Available from: 2019-10-01 Created: 2019-10-01 Last updated: 2020-01-17Bibliographically approved
Bonilla Hernández, A. E., Lu, T., Beno, T., Fredriksson, C. & Jawahir, I. S. (2019). Process sustainability evaluation for manufacturing of a component with the 6R application. Paper presented at Conference of 16th Global Conference on Sustainable Manufacturing, GCSM 2018 ; Conference Date: 2 October 2018 Through 4 October 2018. Procedia Manufacturing, 33, 546-553
Open this publication in new window or tab >>Process sustainability evaluation for manufacturing of a component with the 6R application
Show others...
2019 (English)In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 33, p. 546-553Article in journal (Refereed) Published
Abstract [en]

Sustainability in manufacturing can be evaluated at product, process and system levels. The 6R methodology for sustainability enhancement in manufacturing processes includes: reduced use of materials, energy, water and other resources; reusing of products/components; recovery and recycling of materials/components; remanufacturing of products; and redesigning of products to utilize recovered materials/resources. Although manufacturing processes can be evaluated by their productivity, quality and cost, process sustainability assessment makes it a complete evaluation. This paper presents a 6R-based evaluation method for sustainable manufacturing in terms of specific metrics within six major metrics clusters: environmental impact, energy consumption, waste management, cost, resource utilization and society/personnel health/operational safety. Manufacturing processes such as casting, welding, turning, milling, drilling, grinding, etc., can be evaluated using this methodology. A case study for machining processes is presented as an example based on the proposed metrics. © 2019 The Authors. Published by Elsevier B.V.

National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology; ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-14467 (URN)10.1016/j.promfg.2019.04.068 (DOI)2-s2.0-85068575451 (Scopus ID)
Conference
Conference of 16th Global Conference on Sustainable Manufacturing, GCSM 2018 ; Conference Date: 2 October 2018 Through 4 October 2018
Funder
Knowledge Foundation
Available from: 2019-10-01 Created: 2019-10-01 Last updated: 2020-01-27Bibliographically approved
Bonilla Hernández, A. E. (2018). On cutting tool resource management. (Doctoral dissertation). Trollhättan: University West
Open this publication in new window or tab >>On cutting tool resource management
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The search for increased productivity and cost reduction in machining can be interpreted as desire to increase the Material Removal Rate, , and maximize the cutting tool utilization. The CNC process is complex and involves numerous constraints and parameters; ranging from tolerances to machinability. A well-managed preparation process creates the foundation for achieving a reduction in manufacturing errors and machining time. Along the preparation process of the NC-program, two different studies have been performed and are presented in this thesis. One study examined the CAM programming process from the Lean perspective. The other study includes an evaluation of how the cutting tools are used in terms of and tool utilization. Two distinct combinations of cutting data might provide the same . However, the tool life and machining cost can be different. Therefore, selection of appropriate cutting parameters that best meet all these objectives is challenging. An algorithm for analysis and efficient selection of cutting data for maximal , maximal tool utilization and minimal machining cost has been developed and is presented in this work. The presented algorithm shortens the time dedicated to the optimized cutting data selection and the needed iterations along the program development. Furthermore, the objectives that need to be considered during the estimation of the manufacturing processes sustainability have been identified. In addition, this thesis also includes a theoretical study to estimate energy use, CO2-footprint and water consumption during the manufacture of a workpiece, which can be invaluable for companies in their search for sustainability of their manufacturing processes.

Place, publisher, year, edition, pages
Trollhättan: University West, 2018. p. 108
Series
PhD Thesis: University West ; 16
Keywords
CAM programming; Cutting data; Lean; Manufacturing; Material Removal Rate; Optimization; Tool life; Tool utilization; Tool wear; Sustainability
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology; ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-12240 (URN)978-91-87531-82-8 (ISBN)978-91-87531-81-1 (ISBN)
Public defence
2018-05-08, F104, University West, Trollhättan, 10:15 (English)
Opponent
Supervisors
Available from: 2018-04-12 Created: 2018-04-06 Last updated: 2018-10-26Bibliographically approved
Bonilla Hernández, A. E., Beno, T. & Fredriksson, C. (2017). Energy and Cost Estimation of a Feature-based Machining Operation on HRSA. Paper presented at 24th CIRP Conference on Life Cycle Engineering (CIRP LCE), Kamakura, JAPAN, MAR 08-10, 2017. Procedia CIRP, 61(Supplement C), 511-516
Open this publication in new window or tab >>Energy and Cost Estimation of a Feature-based Machining Operation on HRSA
2017 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 61, no Supplement C, p. 511-516Article in journal (Refereed) Published
Abstract [en]

Forward-looking manufacturing companies aim for sustainable production with low environmental footprint. This is true also for aerospace engine-makers, although their environmental impact mostly occurs during the use-phase of their products. Materials, such as Nickel alloys, are used for special applications where other materials will not withstand tough working conditions in terms of pressure and temperature. Heat Resistant Super Alloys are, however, considered difficult to machine and cutting tools will wear off rapidly. In this paper, a simple way to estimate the energy required, the cost and environmental footprint to produce a work piece using standard engineering software is presented. The results show that for a hypothetical 3 tonne work piece, Inconel 718 will be considerably cheaper and require less water but will require more energy, and has considerably larger CO2 footprint than Waspaloy.

Keywords
Energy use, sustainable consumption and production, production cost, environmental footprint, HRSA, feature based machining
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
urn:nbn:se:hv:diva-11573 (URN)10.1016/j.procir.2016.11.141 (DOI)000404511900089 ()2-s2.0-85020019067 (Scopus ID)
Conference
24th CIRP Conference on Life Cycle Engineering (CIRP LCE), Kamakura, JAPAN, MAR 08-10, 2017
Funder
Knowledge Foundation
Note

Available from: 2017-09-19 Created: 2017-09-19 Last updated: 2020-02-06Bibliographically approved
Bonilla Hernández, A. E., Beno, T., Repo, J. & Wretland, A. (2016). Integrated optimization model for cutting data selection based on maximal MRR and tool utilization in continuous machining operations. CIRP - Journal of Manufacturing Science and Technology, 13, 46-50
Open this publication in new window or tab >>Integrated optimization model for cutting data selection based on maximal MRR and tool utilization in continuous machining operations
2016 (English)In: CIRP - Journal of Manufacturing Science and Technology, ISSN 1755-5817, E-ISSN 1878-0016, Vol. 13, p. 46-50Article in journal (Refereed) Published
Abstract [en]

The search for increased productivity can be interpreted as the increase of material removal rate (MRR). Namely, increase of feed, depth of cut and/or cutting speed. The increase of any of these three variables, will increase the tool wear rate; therefore decreasing its tool life according to the same tool life criteria. This paper proposes an integrated model for efficient selection of cutting data for maximal MRR and maximal tool utilization. The results show that, it is possible to obtain a limited range of cutting parameters from where the CAM Programmer can select the cutting data assuring both objectives.

Keywords
Materials removal rate (MRR), tool life, tool wear, cutting data, optimization
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology; ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-8674 (URN)10.1016/j.cirpj.2016.02.002 (DOI)000376092800005 ()2-s2.0-84960153710 (Scopus ID)
Funder
Knowledge Foundation
Note

Ingår i licentiatuppsats. Available online 12 March 2016

Available from: 2015-11-17 Created: 2015-11-17 Last updated: 2019-12-03Bibliographically approved
Bonilla Hernández, A. E. (2015). Analysis and direct optimization of cutting tool utilization in CAM. (Licentiate dissertation). Trollhättan: University West
Open this publication in new window or tab >>Analysis and direct optimization of cutting tool utilization in CAM
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The search for increased productivity and cost reduction in machining can be interpreted as the desire to increase the material removal rate, MRR, and maximize the cutting tool utilization. The CNC process is complex and involves numerous limitations and parameters, ranging from tolerances to machinability. A well-managed preparation process creates the foundations for achieving a reduction in manufacturing errors and machining time. Along the preparation process of the NC-program, two different studies have been conducted and are presented in this thesis. One study examined the CAM programming preparation process from the Lean perspective. The other study includes an evaluation of how the cutting tools are used in terms of MRR and tool utilization.

The material removal rate is defined as the product of three variables, namely the cutting speed, the feed and the depth of cut, which all constitute the cutting data. Tool life is the amount of time that a cutting tool can be used and is mainly dependent on the same variables. Two different combinations of cutting data might provide the same MRR, however the tool life will be different. Thereby the difficulty is to select the cutting data to maximize both MRR and cutting tool utilization. A model for the analysis and efficient selection of cutting data for maximal MRR and maximal tool utilization has been developed and is presented. The presented model shortens the time dedicated to the optimized cutting data selection and the needed iterations along the program development.

Place, publisher, year, edition, pages
Trollhättan: University West, 2015. p. 82
Series
Licentiate Thesis: University West ; 7
Keywords
CAM programming; Material Removal Rate; Tool life; Tool wear; Tool utilization; Cutting data; Lean; Optimization; CIM; Integration IT tools; Manufacturing
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
urn:nbn:se:hv:diva-8672 (URN)978-91-87531-14-9 (ISBN)978-91-87531-13-2 (ISBN)
Presentation
2015-11-27, C-118, University West, Trollhättan, 10:00 (English)
Opponent
Supervisors
Available from: 2015-11-18 Created: 2015-11-17 Last updated: 2016-11-13Bibliographically approved
Bonilla Hernández, A. E., Beno, T., Repo, J. & Wretland, A. (2015). Analysis of Tool Utilization from Material Removal Rate Perspective. Paper presented at The 22nd CIRP Conference on Life Cycle Engineering, Univ New S Wales, Sydney, AUSTRALIA, APR 07-09, 2015. Procedia CIRP, 29, 109-113
Open this publication in new window or tab >>Analysis of Tool Utilization from Material Removal Rate Perspective
2015 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 29, p. 109-113Article in journal (Refereed) Published
Abstract [en]

An end of life strategy algorithm has been used to study a CNC program to evaluate how the cutting inserts are used in terms of their full utilization. Utilized tool life (UTL) and remaining tool life (RTL) were used to evaluate if the insert has been used to its limits of expected tool life, or contributing to an accumulated tool waste. It is demonstrated that possible means to improvement exists to increase the material removal rate (MRR), thereby using the insert until its remaining tool life is as close to zero as possible. It was frequently found that inserts were used well below their maximum performance with respect to cutting velocity.

Keywords
Tool life, tool utilization, material removal rate (MRR)
National Category
Manufacturing, Surface and Joining Technology Computer Systems
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
urn:nbn:se:hv:diva-7614 (URN)10.1016/j.procir.2015.02.183 (DOI)000356146100019 ()2-s2.0-84939630891 (Scopus ID)
Conference
The 22nd CIRP Conference on Life Cycle Engineering, Univ New S Wales, Sydney, AUSTRALIA, APR 07-09, 2015
Available from: 2015-06-02 Created: 2015-05-30 Last updated: 2020-02-20Bibliographically approved
Bonilla Hernández, A. E., Beno, T., Repo, J. & Wretland, A. Streamlining the CAM programming process by Lean Principles within the aerospace industry.
Open this publication in new window or tab >>Streamlining the CAM programming process by Lean Principles within the aerospace industry
(English)Manuscript (preprint) (Other academic)
Keywords
CAM programming, Lean Principles, Integration IT tool, CIM, Green manufacturing
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-8673 (URN)
Note

Ingår i lic uppsats

Available from: 2015-11-17 Created: 2015-11-17 Last updated: 2020-03-16Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2146-7916

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