Economic Analysis of Technology Infrastructure Needs for Advanced Manufacturing: Smart Manufacturing

Gallaher, Michael; Oliver, Zachary T.; Rieth, Kirsten; O'Connor, Alan C.

doi:10.6028/nist.gcr.16-007

Cited by 16 publications

(13 citation statements)

References 3 publications

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“…At a machine tool level, Machine-to-Machine (M2M) communication protocols, such as MTConnect and OPC UA, have been considered as a potential standard. However, the use of these protocols is limited to certain classes of machines, and small Original Equipment Manufacturers (OEMs) do not have the capability to develop the software functions to integrate them into their product’s control system [46]. As a result, most of the existing manufacturing equipment, especially for SMEs, still do not have the built-in capability to transmit and receive data through a network connection [47].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Vision-Based Monitoring of Computer Numerical Control (CNC) Machine Tools for Small and Medium-Sized Enterprises (SMEs)

Kim

Jung

Choi

et al. 2019

Sensors

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In the new era of manufacturing with the Fourth Industrial Revolution, the smart factory is getting much attention as a solution for the factory of the future. Despite challenges in small and medium-sized enterprises (SMEs), such as short-term strategies and labor-intensive with limited resources, they have to improve productivity and stay competitive by adopting smart factory technologies. This study presents a novel monitoring approach for SMEs, KEM (keep an eye on your machine), and using a low-cost vision, such as a webcam and open-source technologies. Mainly, this idea focuses on collecting and processing operational data using cheaper and easy-to-use components. A prototype was tested with the typical 3-axis computer numerical control (CNC) milling machine. From the evaluation, availability of using a low-cost webcam and open-source technologies for monitoring of machine tools was confirmed. The results revealed that the proposed system is easy to integrate and can be conveniently applied to legacy machine tools on the shop floor without a significant change of equipment and cost barrier, which is less than $500 USD. These benefits could lead to a change of monitoring operations to reduce time in operation, energy consumption, and environmental impact for the sustainable production of SMEs.

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Section: Introductionmentioning

confidence: 99%

A Low-Cost Vision-Based Monitoring of Computer Numerical Control (CNC) Machine Tools for Small and Medium-Sized Enterprises (SMEs)

Kim

Jung

Choi

et al. 2019

Sensors

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“…Further, Anderson (2016) opined that technology infrastructures include foundational technology services, equipment, software facilities and structure upon which the capabilities of an organization are built. Gallaher, Oliver, Reith, and O'Connor (2016) define technology infrastructure as infra-technologies and technology platform which include electricity, defense system, modern transportation, scientific and engineering databases, reference materials, and process models. Scott, Beaulieu, Rothrock, and O'Connor (2016), further asserted that technology infrastructure is a component of competitiveness that gives organization or a nation an edge for investors attraction with combined attributes of stable political environment, language, culture and good quality of life (World Bank Report, 2018).…”

Section: Technology Infrastructurementioning

confidence: 99%

Technology Transfer and Competitive Advantage: The Managers’ Perspective

2019

EJBM

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Achieving and sustaining competitive advantages is becoming extraordinarily difficult as strategic intangible resources are hidden from public consumption and information asymmetry rules a turbulence business environment. The how of competitive advantage debate revolves around different constructs but technology transfer (technology infrastructure, innovation, and adoption) constitutes the focus of this work. The paper argued from technology transfer proxies to explain firms' competitive advantage through the knowledge lenses of managers. Cross-sectional survey research design was adopted, the unit of analysis was randomly selected and data were collected from 90 managers of telecommunication companies in Lagos State, Nigeria through a validated questionnaire whose reliability was established. The study provided empirical evidences that a relationship exist between technology transfer dimensions (technology adoption, technology infrastructure, and technology innovation) and competitive advantage (r =0.582, p<0.05; 0.862, p<0.05; 0.684, p<0.05) and that these further affected significantly firms' competitive advantage (Fstat.19.16, p-value 0.000) among the surveyed companies. The recommendation focused on technology transfer in the form of adoption, infrastructure and innovation within a business ecosystem to promote competitive advantage.

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“…Technology transfer has been noted in different studies as having a significant impact on labour productivity (Gallaher, Oliver, Reith, & O'Connor, 2016). According to Nicodemus and Egwakhe (2019), technology transfer in the form of adoption, infrastructure and innovation within a business ecosystem promotes competitive advantage.…”

Section: Introductionmentioning

confidence: 99%

Can Technology Transfer Stimulate Labour Productivity: Experience from Nigeria Automobile Sector

Egwakhe¹,

Amos²,

Nicodemus³

2020

IJBM

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This paper argued that technology transfer possesses operational and structural capability to stimulate labour productivity in Nigerian automobile sector. Technology transfer proxies are knowledge transfer, skill acquisition, technology infrastructure, innovation, and adoption and their fundamental effect on workforce productivity. A cross-sectional survey research design was adopted to capture the perception of respondents at a categorical point in time. There were three automobile manufacturing companies in Nigeria from which the responding organisations were drawn.  The unit of analysis consisted of 675 managers and engineers who were randomly selected from a total population of 1,150. The research instrument was adapted, and its content and construct validity were established. Also, it was subjected to reliability test with Cronbach’s alpha value above the minimum threshold. The hypothesis was tested using multiple regressions and the aggregate result revealed a positive significant relationship between technology transfer and labour productivity. The power of the individual result revealed that a positive significant relationship exists between the dimensions of technology transfer (skill acquisition, technology infrastructure, technology innovation, technology adoption, and labour productivity, while knowledge transfer was not significant. The study recommended sustained and progressive technology transfer to enhance workers’ productivity in the sector.

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Economic Analysis of Technology Infrastructure Needs for Advanced Manufacturing: Smart Manufacturing

Abstract: Many contributed to the preparation of this report, and we wish to acknowledge in particular the private companies, industry associations, research institutes, universities, and government agencies whose experts contributed data and insights underlying the analysis herein.

Cited by 16 publications

References 3 publications

A Low-Cost Vision-Based Monitoring of Computer Numerical Control (CNC) Machine Tools for Small and Medium-Sized Enterprises (SMEs)

A Low-Cost Vision-Based Monitoring of Computer Numerical Control (CNC) Machine Tools for Small and Medium-Sized Enterprises (SMEs)

Technology Transfer and Competitive Advantage: The Managers’ Perspective

Can Technology Transfer Stimulate Labour Productivity: Experience from Nigeria Automobile Sector

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