Understanding Data-Related Concepts in Smart Manufacturing and Supply Chain Through Text Mining

2021 ◽  
pp. 508-519
Author(s):  
Angie Nguyen ◽  
Juan Pablo Usuga-Cadavid ◽  
Samir Lamouri ◽  
Bernard Grabot ◽  
Robert Pellerin
Keyword(s):  
Supply Chain ◽  
Text Mining ◽  
Smart Manufacturing

Blockchain as supply chain technology: considering transparency and security

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pei Xu ◽  
Joonghee Lee ◽  
James R. Barth ◽  
Robert Glenn Richey
Keyword(s):  
Supply Chain ◽  
Text Mining ◽  
Information Security ◽  
Design Methodology ◽  
Use Cases ◽  
Future Research ◽  
Content Type ◽  
Blockchain Technology ◽  
Twitter Data ◽  
The Way

PurposeThis paper discusses how the features of blockchain technology impact supply chain transparency through the lens of the information security triad (confidentiality, integrity and availability). Ultimately, propositions are developed to encourage future research in supply chain applications of blockchain technology.Design/methodology/approachPropositions are developed based on a synthesis of the information security and supply chain transparency literature. Findings from text mining of Twitter data and a discussion of three major blockchain use cases support the development of the propositions.FindingsThe authors note that confidentiality limits supply chain transparency, which causes tension between transparency and security. Integrity and availability promote supply chain transparency. Blockchain features can preserve security and increase transparency at the same time, despite the tension between confidentiality and transparency.Research limitations/implicationsThe research was conducted at a time when most blockchain applications were still in pilot stages. The propositions developed should therefore be revisited as blockchain applications become more widely adopted and mature.Originality/valueThis study is among the first to examine the way blockchain technology eases the tension between supply chain transparency and security. Unlike other studies that have suggested only positive impacts of blockchain technology on transparency, this study demonstrates that blockchain features can influence transparency both positively and negatively.

Sustainability topic trends in the textile and apparel industry: a text mining-based magazine article analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jitong Li ◽  
Karen K. Leonas
Keyword(s):  
Supply Chain ◽  
Text Mining ◽  
Correlation Coefficients ◽  
Implementation Process ◽  
Apparel Industry ◽  
Sustainable Supply Chain ◽  
Sustainable Practices ◽  
Content Type ◽  
Textile And Apparel ◽  
Textile And Apparel Industry

PurposeThe purpose of this study is to (1) identify the sustainable practices developed by the textile and apparel industry and (2) investigate the gaps and opportunities in the sustainability implementation process by quantitively analyzing the sustainability topics and the relevant topic trends.Design/methodology/approachThis study employed text mining techniques. A total of 1,168 relevant magazine articles published from 2013 to 2020 were collected and then categorized according to their tones. In total, 36 topics were identified by reviewing the sustainability issues in the industry. The frequency of each topic mentioned in the articles and the correlation coefficients between topics' frequencies and published time were calculated. The results were used to examine if the three sustainability dimensions (environment, society, economy) were equally addressed and identify opportunities in the sustainability implementation process.FindingsThere were much fewer social and economic topics than environmental topics discussed in the articles. Additionally, there were not enough practices developed to reduce microfiber pollution, improve consumers' knowledge of sustainability, offset the carbon footprint, build a transparent, sustainable supply chain and avoid animal cruelty.Originality/valueThere is a lack of research focusing on the whole supply chain and sustainability when investigating sustainable practices and topic trends. This study fills a part of the gap. The results can be used by industrialists to identify sustainable practice opportunities and better manage their sustainable supply chains. Researchers can utilize the results to compare the topics in the industry with the topics studied in academia.

scholarly journals Leveraging Flexible Smart Manufacturing to Accelerate Industrial Supply Chain Recovery

2020 ◽  
Vol 4 (3) ◽  
pp. 20200056
Author(s):  
Shane Terry ◽  
Prashant Nagapurkar ◽  
Sujit Das
Keyword(s):  
Supply Chain ◽  
Smart Manufacturing

Manufacturing Services Classification in a Decentralized Supply Chain Using Text Mining

2018 ◽  
pp. 186-193 ◽  
Author(s):  
M. D. Akhtar ◽  
V. K. Manupati ◽  
M. L. R. Varela ◽  
G. D. Putnik ◽  
A. M. Madureira ◽  
...  
Keyword(s):  
Supply Chain ◽  
Text Mining ◽  
Decentralized Supply Chain

scholarly journals Optimal product co-creation strategies in a service-oriented smart manufacturing supply chain

2021 ◽  
Vol 192 ◽  
pp. 1924-1933
Author(s):  
Xiao Zhang ◽  
Xiaoxiao Chang ◽  
Huaqing Qiu ◽  
Lindu zhao
Keyword(s):  
Supply Chain ◽  
Smart Manufacturing ◽  
Manufacturing Supply Chain ◽  
Service Oriented

scholarly journals Traceable and Intelligent Supply Chain based on Blockchain and Artificial Intelligence

2021 ◽  
Vol 2070 (1) ◽  
pp. 012158
Author(s):  
Sachin Karadgi ◽  
Vadiraj Kulkarni ◽  
Shridhar Doddamani
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Manufacturing System ◽  
Smart Manufacturing ◽  
Process Data ◽  
Control Data ◽  
Chain Management ◽  
Manufacturing Enterprises ◽  
Development Lifecycle ◽  
Narrow Context

Abstract Smart manufacturing focuses on maximizing the capabilities to increase multiple objectives, like cost, delivery, and quality, in manufacturing enterprises. This requires implementing product development lifecycle, production system lifecycle, and business cycle for supply chain management. In short, a considerable amount of data is generated in a given manufacturing enterprise. Likewise, progress has been made to adopt blockchain in financial industries, but the adoption is slow in non-financial sectors. The article elaborates a methodology for the realization of a traceable and intelligent supply chain. First, the methodology elaborates on the realization of traceability of enterprise entities, which are an integral part of the supply chain. In this case, each participating stakeholder of the supply chain is required internally to realize a smart manufacturing system with an extension to write critical control data to the blockchain (i.e., a subset of process data). Artificial Intelligence (AI) is being adopted in most industries. A supply chain stakeholder has access to its data and can employ AI to derive new insights. The data available with the stakeholder provides a narrow context. With blockchain, all the stakeholders have access to the data from other stakeholders. Subsequently, the insights derived by a stakeholder will be more meaningful. This will assist in realizing an intelligent supply chain.

Detecting a security breach and pinpointing its source

2020 ◽  
Vol 2020 (1) ◽  
pp. 000067-000072
Author(s):  
Dave Huntley
Keyword(s):  
Supply Chain ◽  
Smart Manufacturing ◽  
Security Threats ◽  
Distributed Network ◽  
Security Attacks ◽  
Aerospace Applications ◽  
Private Data ◽  
Chain Of Custody ◽  
Flow Through ◽  
Data Collections

Abstract There are many rapidly emerging technologies to embed a “Root of Trust” (RoT) in silicon or in assembled packages and PCBs further down the supply chain. These all aim to provide an un-hackable proof of device identity and uncompromised firmware. Despite these efforts we can, and should, assume that bad actors will succeed to counterfeit devices, install malware, etc. So how do we detect and respond to these attacks in time before they cause too much harm? This is, of course, of particular concern for defense and aerospace applications. We will discuss an initiative at SEMI to provide asset traceability through the supply chain. The intention is to detect counterfeits and security attacks quickly, track them back through the supply chain and identify the culprit. The threat of capture and penalties is expected to reduce the incentive for the bad actors in future. The proposed SEMI standard will define the transactions and data required to record chain of custody for electronic assets as they flow through the supply chain. These transactions will be recorded on Hyperledger Fabric, a blockchain platform which offers an immutable transaction ledger, maintained within a distributed network of peer nodes. The ledger will not be public (like bitcoin), nor will it be private to one organization. Instead it will follow a consortium model and be permissioned to support flexible trust assumptions. The SEMI standard will facilitate supply chain members to form one or more consortiums and host the Hyperledger nodes. This will enable the early detection and response to counterfeit and security threats to electronic assets that the supply chain members manufacture or distribute. The standard takes care not to expose any confidential technical or commercial information. However, Hyperledger offers the concepts of private data collections and channels to allow for the sharing of private data between specific members. This could become an enabler to realize the data sharing required to meet Smart Manufacturing 4.0 objectives. There are a number of similar chain of custody ledger initiatives underway both in the commercial and standards arena. The hope is that the SEMI standard will encourage these systems to merge into an industry wide consortium with increased interoperability, performance, reliability and security.

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