A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective

被引:14
作者
Zafarzadeh, Masoud [1 ]
Wiktorsson, Magnus [1 ]
Baalsrud Hauge, Jannicke [1 ,2 ]
机构
[1] KTH Royal Inst Technol, Dept Sustainable Prod Dev, S-11428 Stockholm, Sweden
[2] BIBA Inst, D-28359 Bremen, Germany
来源
LOGISTICS-BASEL | 2021年 / 5卷 / 02期
关键词
data-driven; smart; process automation; production logistics; technology; transition; autonomous systems; BIG DATA ANALYTICS; INDUSTRY; 4.0; SUPPLY CHAIN; MANUFACTURING SYSTEM; REAL-TIME; SMART PRODUCTION; LIFE-CYCLE; IOT; INTERNET; INFORMATION;
D O I
10.3390/logistics5020024
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
A data-driven approach in production logistics is adopted as a response to challenges such as low visibility and system rigidity. One important step for such a transition is to identify the enabling technologies from a value-creating perspective. The existing corpus of literature has discussed the benefits and applications of smart technologies in overall manufacturing or logistics. However, there is limited discussion specifically on a production logistics level, from a systematic perspective. This paper addresses two issues in this respect by conducting a systematic literature review and analyzing 142 articles. First, it covers the gap in literature concerning mapping the application of these smart technologies to specific production logistic activities. Ten groups of technologies were identified and production logistics activities divided into three major categories. A quantitative share assessment of the technologies in production logistics activities was carried out. Second, the ultimate goal of implementing these technologies is to create business value. This is addressed in this research by presenting the "production logistics data lifecycle" and the importance of having a balanced holistic perspective in technology development. The result of this paper is beneficial to build a ground to transit towards a data-driven state by knowing the applications and use cases described in the literature for the identified technologies.
引用
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页数:32
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