scholarly journals Artificial Intelligence in Manufacturing Companies and Broader: An Overview

2019 ◽  
pp. 081-098
Author(s):  
Borut Buchmeister ◽  
Iztok Palcic ◽  
Robert Ojstersek
Keyword(s):  
Artificial Intelligence ◽  
Manufacturing Companies

Automatic information retrievement for exporting services: First project findings from the development of an AI based export decision supporting instrument

2021 ◽  
pp. 2-11
Author(s):  
David Aufreiter ◽  
Doris Ehrlinger ◽  
Christian Stadlmann ◽  
Margarethe Uberwimmer ◽  
Anna Biedersberger ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Research Process ◽  
Training Data ◽  
Future Research ◽  
Manufacturing Companies ◽  
Market Information ◽  
Annotation Scheme ◽  
Export Decisions ◽  
Decision Supporting

On the servitization journey, manufacturing companies complement their offerings with new industrial and knowledge-based services, which causes challenges of uncertainty and risk. In addition to the required adjustment of internal factors, the international selling of services is a major challenge. This paper presents the initial results of an international research project aimed at assisting advanced manufacturers in making decisions about exporting their service offerings to foreign markets. In the frame of this project, a tool is developed to support managers in their service export decisions through the automated generation of market information based on Natural Language Processing and Machine Learning. The paper presents a roadmap for progressing towards an Artificial Intelligence-based market information solution. It describes the research process steps of analyzing problem statements of relevant industry partners, selecting target countries and markets, defining parameters for the scope of the tool, classifying different service offerings and their components into categories and developing annotation scheme for generating reliable and focused training data for the Artificial Intelligence solution. This paper demonstrates good practices in essential steps and highlights common pitfalls to avoid for researcher and managers working on future research projects supported by Artificial Intelligence. In the end, the paper aims at contributing to support and motivate researcher and manager to discover AI application and research opportunities within the servitization field.

scholarly journals Role of Artificial Intelligence in Enhancing Efficiency of Accounting Information System and Non-Financial Performance of the Manufacturing Companies

2021 ◽  
Vol 14 (12) ◽  
pp. 65
Author(s):  
Firas Hashem ◽  
Rateb Alqatamin
Keyword(s):  
Artificial Intelligence ◽  
Financial Performance ◽  
Intelligent Systems ◽  
Accounting Information ◽  
Performance Standards ◽  
Primary Data ◽  
Fiscal Year ◽  
Manufacturing Companies ◽  
Accounting Information System ◽  
The Impact

The current study launched from the main objective of examining the impact of artificial intelligence (AI) and its role in supporting and improving the efficiency of AIS on one hand, and non-financial performance standards on the other. In order to achieve this goal and indicate the extent of its conformity with reality; quantitative approach was used and a questionnaire were adopted as a study tool, the questionnaire was distributed electronically to a sample of (409) managers, heads of departments and accountants in industrial establishments operating in Jordan during the fiscal year 2020/2021. By analyzing the primary data based on SPSS, the study came to the conclusion that AI techniques played a significant role in enhancing efficiency of AIS outcomes through focusing on outcomes' understandability, reliability, credibility and comparability, on another level, AI techniques also proved its ability to influence non-financial performance through focusing on feeding organization with the needed information that locates weak points and develop them, and strength points to exploit them. Study recommended the need to link the operations of intelligent systems to the goals of the organization as a whole and ensure the complete interdependence between the AIS systems and the accounting information in the systems.

scholarly journals The Role of Artificial and Nonartificial Intelligence in the New Product Success with Moderating Role of New Product Innovation: A Case of Manufacturing Companies in China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hou Jianjun ◽  
Yi Yao ◽  
Javaria Hameed ◽  
Hafiz Waqas Kamran ◽  
Muhammad Atif Nawaz ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Product Innovation ◽  
New Product ◽  
Manufacturing Companies ◽  
New Product Success ◽  
Product Success ◽  
Manufacturing Organizations ◽  
New Product Innovation ◽  
Moderating Role

Currently, there is an increasing trend in the organizations towards examining the artificial intelligence and nonartificial intelligence for the innovation and success of the new product, as well as getting the intentions of the upcoming researchers. Thus, the purpose of the ongoing study is to examine the role of artificial and nonartificial intelligence in the new product success along with the moderating role of new product innovation in the manufacturing organizations of China. The quantitative methods have been followed by the study and gathered the responses from the respondents using questionnaires, and analysis has been conducted by using the smart-PLS. The results exposed that artificial intelligence and nonartificial intelligence have positive and significant nexus with the new product success. The outcomes also revealed that the new product innovation significantly moderated the links among the nonartificial intelligence and new product success, but it insignificantly moderated the links among the artificial intelligence and new product success in the manufacturing organizations of China. These findings have provided the guidelines to the manufacturing companies and their policies developing authorities that they should be developed and implement the suitable policies regarding the adoption of artificial intelligence and nonartificial intelligence that enhance the success of the new product, which ultimately enhances the success of the organization.

Artificial Intelligence and Backshoring Strategies

2021 ◽  
pp. 227-255
Author(s):  
Steffen Kinkel ◽  
Mauro Capestro ◽  
Eleonora Di Maria
Keyword(s):  
Artificial Intelligence ◽  
Empirical Evidence ◽  
Industry 4.0 ◽  
Positive Impact ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Production Processes ◽  
Strategic Factors ◽  
Using Data ◽  
The Relationship

The Industry 4.0 technologies, such as artificial intelligence (AI), are transforming the manufacturing processes and affecting the location of manufacturing activities across countries, with a potentially positive impact on the backshoring of production processes. The chapter aims at providing empirical evidence on the relationship between AI and relocation, exploring how AI is related to both the offshoring and backshoring strategies, using data from an international sample of 124 German and Italian manufacturing companies. Following the investigation of AI use by German and Italian manufacturing companies, the study analyses the differences in some strategic factors and the offshoring and backshoring decisions between German and Italian companies, AI users and non-users, and between the German and Italian AI users. Results show that the most important differences concern AI users and non-users and indicate a higher value of AI use for backshoring rather than offshoring strategies. The findings enable the derivation of both theoretical and managerial contributions.

scholarly journals Artificial Intelligence Applications for Increasing Resource Efficiency in Manufacturing Companies—A Comprehensive Review

2021 ◽  
Vol 13 (12) ◽  
pp. 6689
Author(s):  
Lara Waltersmann ◽  
Steffen Kiemel ◽  
Julian Stuhlsatz ◽  
Alexander Sauer ◽  
Robert Miehe
Keyword(s):  
Artificial Intelligence ◽  
Resource Efficiency ◽  
Ecological Crisis ◽  
Manufacturing Companies ◽  
Potential Influence ◽  
Business Units ◽  
Predictive Quality ◽  
Ecological Performance ◽  
Use Phase ◽  
Meta Analyses

Sustainability improvements in industrial production are essential for tackling climate change and the resulting ecological crisis. In this context, resource efficiency can directly lead to significant advancements in the ecological performance of manufacturing companies. The application of Artificial Intelligence (AI) also plays an increasingly important role. However, the potential influence of AI applications on resource efficiency has not been investigated. Against this background, this article provides an overview of thecurrent AI applications and how they affect resource efficiency. In line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this paper identifies, categorizes, and analyzes seventy papers with a focus on AI tasks, AI methods, business units, and their influence on resource efficiency. Only a minority of papers was found to address resource efficiency as an explicit objective. Subsequently, typical use cases of the identified AI applications are described with a focus on predictive maintenance, production planning, fault detection and predictive quality, as well as the increase in energy efficiency. In general, more research is needed that explicitly considers sustainability in the development and use phase of AI solutions, including Green AI. This paper contributes to research in this field by systematically examining papers and revealing research deficits. Additionally, practitioners are offered the first indications of AI applications increasing resource efficiency.

scholarly journals ARTIFICIAL INTELLIGENCE APPLICATION AND ORGANIZATIONAL EFFICIENCY IN MANUFACTURING SECTOR IN RIVERS STATE

2021 ◽  
pp. 22-33
Author(s):  
Lemue BEKURU ◽  
Patrick NWINYOKPUGI
Keyword(s):  
Artificial Intelligence ◽  
Manufacturing Sector ◽  
Predictor Variable ◽  
Hazardous Substances ◽  
Correction Coefficient ◽  
Organizational Efficiency ◽  
Manufacturing Companies ◽  
Rivers State ◽  
Artificial Intelligence Application ◽  
Intelligence Application

The study was to investigate the relationship between artificial intelligence application and organizational efficiency in manufacturing sector in Rivers State. A descriptive research survey design was used for the study. The sample of the study is six (6) operational managers from each of the twenty six (26) registered manufacturing companies in Rivers state by manufacturing association of Nigeria (MAN) Rivers state chapter. The population of the study is twenty six (26) registered operational manufacturing companies in Rivers state. The researcher distributed 156 questionnaires to the respondents. The method of data collection was through questionnaires. Data from the distributed questionnaires was further analyzed, using the Pearson Product Moment Correction Coefficient. The hypotheses of the study were tested using Pearson’s product moment Correlation with aidof the statistical package for social science (SPSS). Findings revealed that, the predictor variable artificial intelligence and its dimension robotics, and electronic fund transfer have significant relationship with the measures of the criterion variable as innovation and cost reduction. Therefore, it was recommended among others that manufacturing sector should adopt the use of robot in their production process to bring about safety of their staff that might be working hazardous substances and in high risk sections of an organization.

scholarly journals Role of Artificial Intelligence in Enhancing Efficiency of Accounting Information System and Non-Financial Performance of the Manufacturing Companies

2021 ◽  
Vol 14 (12) ◽  
pp. 51
Author(s):  
Firas Hashem ◽  
Rateb Alqatamin
Keyword(s):  
Artificial Intelligence ◽  
Financial Performance ◽  
Intelligent Systems ◽  
Accounting Information ◽  
Performance Standards ◽  
Primary Data ◽  
Fiscal Year ◽  
Manufacturing Companies ◽  
Accounting Information System ◽  
The Impact

The current study launched from the main objective of examining the impact of artificial intelligence (AI) and its role in supporting and improving the efficiency of AIS on one hand, and non-financial performance standards on the other. In order to achieve this goal and indicate the extent of its conformity with reality; quantitative approach was used and a questionnaire were adopted as a study tool, the questionnaire was distributed electronically to a sample of (409) managers, heads of departments and accountants in industrial establishments operating in Jordan during the fiscal year 2020/2021. By analyzing the primary data based on SPSS, the study came to the conclusion that AI techniques played a significant role in enhancing efficiency of AIS outcomes through focusing on outcomes' understandability, reliability, credibility and comparability, on another level, AI techniques also proved its ability to influence non-financial performance through focusing on feeding organization with the needed information that locates weak points and develop them, and strength points to exploit them. Study recommended the need to link the operations of intelligent systems to the goals of the organization as a whole and ensure the complete interdependence between the AIS systems and the accounting information in the systems.

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