Digitalization Technologies for Industrial Sustainability

Demartini, Melissa; Evans, Steve; Tonelli, Flavio

doi:10.1016/j.promfg.2019.04.032

Cited by 68 publications

(36 citation statements)

References 10 publications

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“…The share of research and development (Х24), the effectiveness of the management system (Х25), working conditions (Х26), information security (Х27) *Compiled based on literary sources (Husgafvel et al, (2017) [8]; Demartini et al, (2019) [4]; Yachmeneva et al, (2019) [20] and the expert survey.…”

Section: Compiled Based Onmentioning

confidence: 99%

“…The study applied a four-level hierarchy of input data. All variables that are at the tops of the Fuzzy inference tree by levels from fourth to first are linguistic: R, K={(Ki)1 2 }, Z={(Zi)1 6 }, Y={(Yi)1 4 }, X={(Xi)1 27 }. The following measurement scales were used to adequately reflect the correspondence of qualitative indicators to the characteristics of real objects: five-level (for linguistic variable R: low, below average, medium, above average, high) and three-level (for all others: low, average, high).…”

Section: Fig 2 Algorithmic Model Of the Decision-making Process On Development Taking Into Account Subject-mentioning

confidence: 99%

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Air and space vehicle production: indicators of innovative activity

Кукарцев¹,

Ступина²,

Tynchenko³

et al. 2021

EA-XXI

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We analyze the problems of increasing the innovative activity of air and space vehicle manufacturing enterprises in Russia by the year 2021 and consider indicators reflecting the innovative activity of organizations, such as the implementation of innovations, the proportion of organizations engaged in technological innovation, cost of technological innovation by the source of funds, the dynamics of the innovative production output. Besides, correlation analysis of the relationship between the main indicators of innovation activity and the intensity of expenditures on technological innovations has been performed to identify dependencies describing air and space vehicle production’s distinctive features.

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Section: Compiled Based Onmentioning

confidence: 99%

Section: Fig 2 Algorithmic Model Of the Decision-making Process On Development Taking Into Account Subject-mentioning

confidence: 99%

Air and space vehicle production: indicators of innovative activity

Кукарцев¹,

Ступина²,

Tynchenko³

et al. 2021

EA-XXI

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show abstract

“…An analysis of economic, environmental and social studies by scholars in the field of industrial business [15]- [19] allowed the authors to form 8 groups of indicators that determined the level of adaptive development of an industrial enterprise (R) ( Table I). We used a nested group system such as Resources (Y 1 ), Policy & Legal Environment (Y 2 ) for External Effects (Z 2 ) and Products (Y 3 ), Technologies & Equipment (Y 4 ) for Manufacturing System (Z 3 ).…”

Section: B Performing Operations Of the Algorithm Blocksmentioning

confidence: 99%

Industrial Enterprise Development Management under Digitalization

Veretyokhin*,

Yachmeneva

2020

IJRTE

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The development of an industrial enterprise in order to meet modern requirements should include the components of its digitalization. In Russia, the development of digitalization is supported at the state level. Meantime, limited resources require industrial enterprises to have a sound approach to choosing the direction of their development. This paper presents a methodology for choosing the direction of development of an industrial enterprise, which is based on an assessment of the level of development of that enterprise. An assessment of the level of corporate development is carried out using the method of fuzzy logic and the method of expert assessments. A nonlinear algorithm was used to find an integral indicator of the level of development of an industrial enterprise and choose a direction of development. The assessment process is digitalized and does not require special knowledge and skills of the corporate employees for its implementation. At the same time, it is possible to make adjustments to the indicators that determine the level of development of the industrial enterprise. An assessment of the level of development of an industrial enterprise is implemented in the original InfoLogicTools application in the MathCad simulation environment. Production tests of this application at existing industrial enterprises have allowed making some design changes to the application. The proposed methodology has a practical application. It allowed 3 Russian engineering plants to monitor their development. The monitoring results formed the basis for development activities. Further research is supposed to analyze and develop digitalization of the collection of information on the development of the enterprises.

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“…The digital analysis methodology is applicable to the economy as a whole, and not to individual sectors, since at this stage, it is important to establish the overall level of digitalization of the economy and the development of a digital culture, which is expressed in the systematic adoption of management decisions based on the collection of a large data array using computer technology. My unique study significantly contributes to the existing body of high-quality research on the issues of digital technologies, digital economy, informatization [1], [2], [3], [4], [5], [6], [7].…”

Section: Introductionmentioning

confidence: 97%

Digital analysis as a tool for assessing regional opportunities for the transition to digital technologies

Manzhosova¹

2019

Proceedings of the International Conference on Sustainable Development of Cross-Border Regions: Economic, Social and Security C

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The study presents a digital analysis technique consisting of seven successively implemented blocks, the analytical potential of which allows one to systematically assess the impact of digitalization processes on the regional economy, the readiness to introduce new digital technologies, the degree of innovation activity of economic entities. More than that, this technique allows to determine the presence of deficiencies in the resources that prevent to digital technology. The method of digital analysis can be used to correct the current policy in the field of production modernization, to make management decisions in terms of prospects, and the readiness of transition of individual economic entities to the systemic application of digital technologies, to form data for developing regional modernization programs. The advantage of this methodology is the use of a variety of assessment indicators: quantitative and qualitative, financial and non-financial, sectoral and general economic, absolute and relative, characterizing both the internal and external environment, which allows to reveal obvious and hidden relationships between the processes of digital modernization at the macro and micro levels, unleash the existing potential, and determine the direction of further modernization, identify the current technological state of the economy. The methodological support is built on the basis of individual elements of the "Pattern" method, which makes it possible to identify asymmetry in the digital development of regions and subsequently provide information on the presence of regional competitive advantages for the introduction of digital technologies.

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Digitalization Technologies for Industrial Sustainability

Cited by 68 publications

References 10 publications

Air and space vehicle production: indicators of innovative activity

Air and space vehicle production: indicators of innovative activity

Industrial Enterprise Development Management under Digitalization

Digital analysis as a tool for assessing regional opportunities for the transition to digital technologies

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