A review of energy consumption and minimisation strategies of machine tools in manufacturing process

Yusuf, Lukman; Popoola, Kayode; Musa, Haruna

doi:10.1080/19397038.2021.1964633

Cited by 13 publications

(4 citation statements)

References 74 publications

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“…However, the studied machine tools are not only CNC machines or conventional machines but also flexible and reconfigurable machine tools. Yusuf et al conducted a review of energy saving models and their implementation for energy minimization problems in production and scheduling [ 31 ]. Strategies to minimize energy consumption are also discussed and minimization energy models due to the transient state of machine tools need more efforts to achieve sustainable manufacturing.…”

Section: Preceding Review Studiesmentioning

confidence: 99%

Optimization techniques for energy efficiency in machining processes—a review

abdelaoui

Jabri

Barkany

2023

Int J Adv Manuf Technol

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Metal working process is one of the main activities in mechanical manufacturing industry; it is considered as a major consumer of energy and natural resources. In material removal process, the selection of cutting parameters and cooling or cutting liquid is necessary to save energy and achieve energy efficiency as well as sustainability. During the last two decades, the number of publications in this field has rapidly increased and has shown the importance of this research area. This review paper identifies and reviews in detail a total of 166 scientific studies which exhibit original contributions to the field and address multiple energy efficiency challenges. The recently developed models of energy consumption and different materials used in the machining process are presented. Therefore, this study describes various techniques for modeling and optimizing machining operations such as turning, milling, and drilling. Modeling techniques, experimental methods, multi-objective and single-objective optimization methods, and hybrid techniques optimization are presented in a detailed manner compared to previous review papers where only energy models are discussed. It can help practitioners and researchers to select the most appropriate approach for the desired experience and to highlight the progress of these methods in terms of machining energy efficiency. Additionally, this paper provides a review of different cutting fluids adopted in machining processes. This paper assists researchers and manufacturers in making advantageous technical decisions that have substantial economics in terms of energy saving.

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Section: Preceding Review Studiesmentioning

confidence: 99%

Optimization techniques for energy efficiency in machining processes—a review

abdelaoui

Jabri

Barkany

2023

Int J Adv Manuf Technol

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“…The solution constraints are associated with the dynamic decision-making software of the target architecture, which guarantee the efficiency of the presented solution [43][44][45][46]. For example, being generic and specific means that the software should be generic enough to be configurable for different companies, but have the required configuration parameters, to make it specific for each company.…”

Section: Fig 2 Motivation and Strategy Layersmentioning

confidence: 99%

Towards a Reference Architecture for Planning and Control Services

Pourmehdi

Iacob

Mes

2023

Lecture Notes in Business Information Processing

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Producers of manufacturing equipment can, instead of just selling their products, also offer their customers services to increase customer satisfaction, gain competitive advantage, and increase their profits. These goals can be reached by helping the customers optimise their processes and improve their reliability and flexibility. This can be done by supporting the customer that invests in new manufacturing machines with a planning and control tool connecting the machines and the processes between them. More specifically, this will become possible by introducing and integrating active data management and analysis, and planning applications in the current architecture of companies. All of the processes currently being done manually in the customer companies, from monitoring to production planning based on direct observation and the experience of production managers, can be automated using these applications. This paper presents a reference architecture supporting the connection of these processes using the mentioned applications, and validates the developed models based on a real case study of a production machine manufacturer and its customers.

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“…Pendugaan (prediksi) kebutuhan daya listrik untuk pembuatan suatu perangkat produksi menjadi sangat penting, agar biaya konsumsi daya listrik dapat diantisipasi dan diinternalisasi menjadi biaya produksi [1,2]. Daya listrik terkonsumsi untuk pembuatan setiap generator penghasil gas oksigen (generator oksigen) bukan menjadi hal utama, namun keberadaan daya terkonsumsi tersebut tetap harus diperhitungkan [3].…”

Section: Pendahuluanunclassified

Pendugaan Kebutuhan Daya Listrik Berbantuan Metode Linearisasi Fungsi Nonlinear Untuk Produksi Sebuah Generator Oksigen

Maulana,

Goeritno

2022

Transmisi J.Ilm. Tek. Elekt.

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Kebutuhan daya listrik untuk pembuatan suatu peralatan produksi menjadi sangat penting, agar biaya konsumsi daya listrik dapat diantisipasi dan diinternalisasi menjadi biaya produksi. Daya listrik terkonsumsi untuk pembuatan setiap generator oksigen bukan menjadi hal utama, namun keberadaan unsur tersebut tetap harus diperhitungkan. Berdasarkan hal itu, maka pada penelitian ini diprediksi kebutuhan daya listrik untuk produksi sebuah generator oksigen. Prediksi kebutuhan daya listrik dilakukan dengan metode konvensional berbasis deret waktu, sehingga diperlukan penetapan dua sasaran penelitian yang meliputi (i) mengukur nilai tegangan, mengukur nilai arus, dan menghitung daya untuk kebutuhan fase perakitan dan produksi dan (ii) membuat persamaan regresi linear kebutuhan daya listrik dan menguji kevalidan koefisien korelasi berbantuan metode linearisasi fungsi nonlinear. Metode penelitian dilakukan dengan (i) pencatatan nilai tegangan dan arus, dilanjutkan dengan penghitungan daya listrik terkonsumsi saat fase perakitan dan proses produksi; dan (ii) pembuatan persamaan regresi linear melalui tahapan linearisasi fungsi nonlinear untuk perolehan penggambaran suatu hubungan satu variabel bebas (predictor, x) dengan suatu variabel tak-bebas (response, y), dilanjutkan tahapan perolehan dan uji validitas terhadap koefisien korelasi. Hasil pengukuran tegangan dan arus bervariatif saat fase perakitan maupun saat proses produksi, kemudian dilakukan perhitungnan daya listrik dengan hukum Ohm. Saat fase perakitan, setelah melalui proses linearisasi fungsi nonlinear diperoleh persamaan atau dalam bentuk persamaan regresi linear , dan nilai koefisien korelasi, r sebesar -0,86635. Saat fase proses produksi, setelah dilakukan proses linearisasi fungsi nonlinear diperoleh persamaan atau dalam bentuk persamaan regresi linear, yaitu , dan nilai koefisien korelasi, r sebesar -0,36831. Berdasarkan hasil-hasil tersebut dapat disimpulkan, bahwa koefisien korelasi yang diperoleh telah sesuai persyaratan pada kisaran nilai , namun terkategori dengan kriteria “hubungan kuat” saat fase perakitan dan kriteria “hubungan lemah” saat fase proses produksi. Kriteria “hubungan kuat” pada fase perakitan, disebabkan oleh jumlah peralatan listrik untuk fase perakitan hanya terdiri atas tiga macam peralatan listrik, sedangkan kriteria “hubungan lemah” pada fase proses produksi, disebabkan oleh jumlah peralatan listrik untuk fase proses produksi sebanyak sepuluh peralatan atau berjumlah tiga kali lipat lebih dari fase perakitan.

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A review of energy consumption and minimisation strategies of machine tools in manufacturing process

Cited by 13 publications

References 74 publications

Optimization techniques for energy efficiency in machining processes—a review

Optimization techniques for energy efficiency in machining processes—a review

Towards a Reference Architecture for Planning and Control Services

Pendugaan Kebutuhan Daya Listrik Berbantuan Metode Linearisasi Fungsi Nonlinear Untuk Produksi Sebuah Generator Oksigen

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