Evaluation of smart manufacturing performance using a grey theory-based approach: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anilkumar Malaga ◽  
S. Vinodh

PurposeThe purpose of the article is to report a study on evaluation of smart manufacturing (SM) performance using a grey theory-based approach.Design/methodology/approachIn total, 30 criteria and 79 attributes for SM performance have been developed. A grey theory-based approach has been used for SM performance evaluation. The grey index has been calculated, and weaker areas have been derived. Performance level of SM has been evaluated using the Euclidean distance approach.FindingsThe SM performance index is found to be (3.036, 12.296). The ideal grey performance importance index (GPII) is obtained as (3.025, 4.875). The level of visibility and traceability, vertical integration, lead time and configuration data espionage and control ability are strong performing attributes. Integration abilities of services and manufacturing systems, ability of self-control, worker and raw material productivity, collaboration among buyers and suppliers and dynamic scheduling are identified as weaker areas, and suggestions for improvement have been derived. SM performance level has been identified as “Good.”Research limitations/implicationsAdditional performance measures could be included as a part of evaluation. Practitioners can overcome weaker areas in the early phase. Management achieves confidence and practitioners attain success in implementation of SM in industry through the developed SM performance indexing system.Originality/valueIdentification of SM performance measures and analysis of SM performance is the original contribution of the authors. The developed approach assists practitioners and managers to focus more on specific areas for performance improvement.

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ravinder Kumar ◽  
Rahul Sindhwani ◽  
Punj Lata Singh

Purpose The purpose of this methodology is to categorise the challenges into cause and effect group. The modern scenario of customization, personalization and multi-restrictive working because of pandemics has affected the operations of manufacturing small and medium enterprises (SMEs). In the new normal, the digitalization of manufacturing SMEs can be the path breaker. Modern digitalization includes a mix of technologies such as the industrial internet of things (IIoT), the internet of things, cyber-physical system and big data analytics. This digitalization can help in achieving new design changes, efficient production scheduling, smart manufacturing and unrestricted on-time delivery of quality products. This research paper aims to recognize and analyze the challenges faced while implementing IIoT technologies in manufacturing SMEs and tries to find the possibility of mitigating challenges by blockchain technology. Design/methodology/approach There were ten challenges of IIoT implementation identified from the literature review and experts’ opinions. To collect information from Indian manufacturing SMEs, a survey tool was formed in the form of a questionnaire. On the fundament of responses received from industrial experts, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique has been used for categorizing these challenges into cause and effect groups. Further, the authors tried to mitigate observed challenges with the help of blockchain technology. Findings With the implementation of IIoT technologies, the manufacturing processes become conciliatory, effective and traceable in real time. Observation of the current study states that the top effect group challenges such as the security of data and reliability of technologies can be mitigated by enabling blockchain technologies. The authors conclude that blockchain-enabled IIoT technologies will be highly beneficial for the Indian SMEs strategically and practically in the current scenario. Research limitations/implications Methodology of DEMATEL focuses on responses received from experts. The broader approach of survey from manufacturing organizations is compromised due to small sample size in this methodology. Experts approached for survey were from manufacturing SMEs of Delhi National Capital Region only. Broader survey-based techniques may be applied covering different sectors of SMEs in future work. Practical implications Technologies such as blockchain can facilitate advanced security in the application of IIoT and other such practices. While dealing with significant issues and challenges of new technologies, blockchain gives an edge of balance in the current scenario. Its properties of fixity, temper evident and circumvent fraud make this technology ideal for the digitalization of the manufacturing systems in SMEs. Originality/value Digitalization of manufacturing facilities is the need of the hour. Pandemic challenges have highlighted the urgency of it. This research will motivate and guide the manufacturing SMEs in planning strategies and long-term policies in implementing modern technologies and coping up with the pandemic challenges.


2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Soojeen Jang ◽  
Yanghon Chung ◽  
Hosung Son

PurposeThrough the resource-based view (RBV) and contingency theory, this study empirically investigates the impacts of smart manufacturing systems' maturity levels on the performance of small and medium-sized enterprises (SMEs). Moreover, it aims to examine how industry types (i.e. high- and low-tech industries) and human-resource factors (i.e. the proportion of production workers to total workers) as contingency factors influence the effects of smart manufacturing systems.Design/methodology/approachThe study conducted an empirical investigation of a sample of 163 Korean manufacturing SMEs. This study used an ordinary least squares regression to examine the impacts of the maturity levels of smart manufacturing systems on financial performance. Moreover, the impacts on operational efficiency were analysed using data envelopment analysis based on bootstrap methods and Tobit regression.FindingsThe RBV results indicate that the higher the maturity levels of smart manufacturing systems, the higher the financial performance and operational efficiency. Moreover, based on contingency theory, this study reveals that the effect of the maturity levels of smart manufacturing systems on financial performance and operational efficiency depends on firms' industry types and the proportion of production workers.Research limitations/implicationsThis study shows that the introduction of smart manufacturing systems can help SMEs achieve better financial performance and operational efficiency. However, their effectiveness is contingent on firms' industry types and the characteristics of their human resources.Practical implicationsSince the effects of the maturity levels of smart manufacturing systems on SME performance differ depending on their industries and the characteristics of human resources, managers need to consider them when introducing or investing in smart manufacturing systems.Originality/valueBased on the RBV and contingency theory, this is the first empirical study to examine the moderating effects of industry types and the proportion of production workers on the impacts of the maturity levels of smart manufacturing systems on the financial performance and operational efficiency of SMEs.


2018 ◽  
Vol 24 (9) ◽  
pp. 1486-1499 ◽  
Author(s):  
Hyoung Seok Kang ◽  
Sang Do Noh ◽  
Ji Yeon Son ◽  
Hyun Kim ◽  
Jun Hee Park ◽  
...  

PurposeIn this paper, a three-dimensional (3D) printer-based manufacturing line and supporting system, which supports personalized/customized manufacturing for individual businesses or start-up companies, was studied to evaluate the practicality of using additive manufacturing for personalization/mass customization.Design/methodology/approachFirst, factory-as-a-service (FaaS) system, which provides factory as a service to customers, was proposed and designed to manufacture various products within a distributed manufacturing environment. This system includes 3D printer-based material extrusion processes, vapor machine/computer numerical control machines as post-processes and assembly and inspection processes with an automated material handling robot in the factory. Second, a virtualization module for the FaaS factory was developed using a simulation model interfaced with a cloud-based order and production-planning system and an internet-of-things-based control and monitoring system. This is part of the system for manufacturing operations, which is capable of dynamic scheduling in a distributed manufacturing environment. In addition, simulation-based virtual production was conducted to verify and evaluate the FaaS factory for the target production scenario. Main information of the simulation also has been identified and included in the virtualization module. Finally, the established system was applied in a sample production scenario to evaluate its practicality and efficiency.FindingsAdditive manufacturing is a reliable, feasible and applicable technology, and it can be a core element in smart manufacturing and the realization of personalization/mass customization.Originality/valueVarious studies on additive manufacturing have been conducted with regard to replacing the existing manufacturing methods or integrating with them, but these studies mostly focused on materials or types of additive manufacturing, with few advanced or applied studies on the establishment of a new manufacturing environment for personalization/mass customization.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhiting Song ◽  
Jianhua Zhu

Purpose Smart manufacturing is the prime gripper for the transformation and upgrading of the manufacturing industry. Smart manufacturing systems (SMSs) largely determine how smart manufacturing evolves in technical and organizational dimensions and how it realizes values in products, production or services. SMSs are growing rapidly and receiving tons of attention from academic research and industrial practice. However, the development of SMSs is still in its fancy, and many issues wait to be identified and solved, such as single point failures, low transparency and ineffective resource sharing. Blockchain, an emerging technology deriving from Bitcoin, is competent to aid SMSs to conquer troubles due to its decentralization, traceability, trackability, disintermediation, auditability and etc. The purpose of this paper is to investigate the blockchain applications in SMSs, seek out the challenges faced by blockchain-enabled SMSs (BSMSs) and provide referable research directions and ideas. Design/methodology/approach A comprehensive literature review as a survey is conducted in this paper. The survey starts by introducing blockchain concepts, followed by the descriptions of a literature review method and the blockchain applications throughout the product life cycle in SMSs. Then, the key issues and challenges confronting BSMSs are discussed and some possible research directions are also proposed. It finally presents qualitative and quantitative descriptions of BSMSs, along with some conclusions and implications. Findings The findings of this paper present a deep understanding about the current status and challenges of blockchain adoption in SMSs. Furthermore, this paper provides a brand new thinking for future research. Originality/value This paper minutely analyzes the impacts that blockchain exerts on SMSs in view of the product life cycle, and proposes using the complexity science thinking to deal with BSMSs qualitatively and quantitatively, including tackling the current major problems BSMSs face. This research can serve as a foundation for future theoretical studies and enterprise practice.


2006 ◽  
Vol 55 (3/4) ◽  
pp. 284-299 ◽  
Author(s):  
Peter Nyhuis ◽  
Markus Vogel

PurposeTo provide a model for precise logistic controlling of one‐piece flow processes and for the description of the interactions between logistic performance measures. The developed method can help manufacturing enterprises to control their production processes and therewith to exploit existing rationalization potentials in their production.Design/methodology/approachThe Institute of Production System and Logistics adapted the logistic operating curve for schedule reliability and the logistic operating curve for mean throughput time to describe the behaviour of one‐piece flow processes. This model‐based method depicts the correlation between the delivery reliability and mean WIP level of single manufacturing systems and enables a goal‐oriented modelling as well as a controlling of single manufacturing processes.FindingsThe derivation, calculation, and fields of application of the logistic operating curves for one‐piece flow processes, that give a functional relationship between mean WIP, mean throughput time and schedule reliability, are presented in this paper. Moreover, the paper presents how the logistic performance measures can be adjusted to target values.Originality/valueThis paper offers practical help to manufacturing enterprises confronted with the task of evaluation and optimization of manufacturing processes within the framework of production controlling. Moreover, the developed method enables manufacturing enterprises to identify bottleneck work systems where action can be taken to optimize their schedule situation and thereby improve the delivery reliability of an entire manufacturing department.


2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Weixin Xu ◽  
Huihui Miao ◽  
Zhibin Zhao ◽  
Jinxin Liu ◽  
Chuang Sun ◽  
...  

AbstractAs an integrated application of modern information technologies and artificial intelligence, Prognostic and Health Management (PHM) is important for machine health monitoring. Prediction of tool wear is one of the symbolic applications of PHM technology in modern manufacturing systems and industry. In this paper, a multi-scale Convolutional Gated Recurrent Unit network (MCGRU) is proposed to address raw sensory data for tool wear prediction. At the bottom of MCGRU, six parallel and independent branches with different kernel sizes are designed to form a multi-scale convolutional neural network, which augments the adaptability to features of different time scales. These features of different scales extracted from raw data are then fed into a Deep Gated Recurrent Unit network to capture long-term dependencies and learn significant representations. At the top of the MCGRU, a fully connected layer and a regression layer are built for cutting tool wear prediction. Two case studies are performed to verify the capability and effectiveness of the proposed MCGRU network and results show that MCGRU outperforms several state-of-the-art baseline models.


2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.


2021 ◽  
Vol 11 (7) ◽  
pp. 3186
Author(s):  
Radhya Sahal ◽  
Saeed H. Alsamhi ◽  
John G. Breslin ◽  
Kenneth N. Brown ◽  
Muhammad Intizar Ali

Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry.


2018 ◽  
Vol 8 (3) ◽  
pp. 293-304 ◽  
Author(s):  
Chukwuka Christian Ohueri ◽  
Wallace Imoudu Enegbuma ◽  
Ngie Hing Wong ◽  
Kuok King Kuok ◽  
Russell Kenley

Purpose The purpose of this paper is to develop a motivation framework that will enhance labour productivity for Iskandar Malaysia (IM) construction projects. The vision of IM development corridor is to become Southern Peninsular Malaysia’s most developed region by the year 2025. IM cannot realise this foresight without effective labour productivity. Previous studies have reported that the labour productivity of IM construction projects was six times lower than the labour productivity of Singapore construction projects, due to lack of motivation among IM labourers, and a shortage of local skilled labour. Therefore, there is a need to study how to motivate IM construction labourers, so as to increase their productivity. Design/methodology/approach A quantitative research method was used to collect data from IM construction skilled labourers and construction professionals, using two sets of questionnaire. The respondents were selected using a purposive sampling technique. In total, 40 skilled labourers and 50 construction professionals responded to the questionnaire survey, and the data were analysed using Statistical Package for Social Science software (version 22). Findings The analysis revealed the major factors that motivate labourers participating in IM construction projects. The factors were ranked hierarchically using Relative Importance Index (RII) and the outcome of the ranking indicated that effective management, viable construction practices, financial incentives, continuous training and development, and safe working environment were the most significant motivation strategies that positively influence IM construction labourers. Originality/value The study developed and validated a framework that can be used to boost the morale of IM construction labourers, so that their productivity can be increased. Implementation of the established motivation framework will also lead to career progression of IM construction labourers, based on the training elements in the framework. This career prospect will attract local skilled labourers to participate in IM construction projects.


Sign in / Sign up

Export Citation Format

Share Document