Mitigating risks of perishable products in the cyber-physical systems based on the extended MRP model

Bogataj, David; Bogataj, Marija; Hudoklin, Domen

doi:10.1016/j.ijpe.2017.06.028

Cited by 78 publications

(42 citation statements)

References 49 publications

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“…A promising area of research is that of quality-controlled logistics (QCL). QCL allows dynamic and real-time quality control of products as they move through the supply chain (Giannakourou and Taoukis 2003;Dada and Thiesse 2008;Jedermann and Lang 2008;Osvald and Stirn 2008;Bowman et al 2009;Van der Vorst, Kooten, and Luning 2011;Haass et al 2015;Lang and Jedermann 2015;Pang et al 2015;Tadejko 2015;Bogataj, Marija, and Domen 2017;Heising, Claassen, and Dekker 2017). Bowman et al (2009) point to the challenge of having different sensing and measurement standards across the supply chain.…”

Section: Delivermentioning

confidence: 99%

Internet of things and supply chain management: a literature review

Ben‐Daya

Hassini

Bahroun

2017

International Journal of Production Research

828

527

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This paper explores the role of Internet of Things (IoT) and its impact on supply chain management (SCM) through an extensive literature review. Important aspects of IoT in SCM are covered including IoT definition, main IoT technology enablers and various SCM processes and applications. We offer several categorisation of the extant literature, such as based on methodology, industry sector and focus on a classification based on major supply chain processes. In addition, a bibliometric analysis of the literature is also presented. We find that most studies have focused on conceptualising the impact of IoT with limited analytical models and empirical studies. In addition, most studies have focused on the delivery supply chain process and the food and manufacturing supply chains. Areas of future SCM research that can support IoT implementation are also identified.

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Section: Delivermentioning

confidence: 99%

Internet of things and supply chain management: a literature review

Ben‐Daya

Hassini

Bahroun

2017

International Journal of Production Research

828

527

View full text Add to dashboard Cite

show abstract

“…Later, calculate the initial weight coefficient w i and normalized weight coefficient w i according to formulas (1)(2) and (1)(2)(3).…”

Section: Scalementioning

confidence: 99%

“…When CR < 0.1, it is generally considered that the judgment matrix has satisfactory consistency. Among them, RI is random consistency index, and corresponding value is shown as Table 3; the calculation process CI is shown as the following formulas (1-4), (1)(2)(3)(4)(5) and (1)(2)(3)(4)(5)(6). n is the sub-object number in hierarchy to be checked; λ max is the maximum characteristic root, and λ i is the characteristic root of judgment matrix with pairwise comparison of sub-object in this hierarchy.…”

Section: Scalementioning

confidence: 99%

“…According to formulas (1-4), (1)(2)(3)(4)(5) and (1)(2)(3)(4)(5)(6), calculate the consistency index CI of judgment matrix, and further obtain random consistency ratio CR of each judgment matrix by integrating corresponding random consistency index RI with same order, which is shown as Table 4. CR value of each matrix is less than 0.1, and it is thus clear that the above index weight obtained from grading by experts is effective.…”

Section: Scalementioning

confidence: 99%

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A nonlinear empirical analysis on influence factor of circulation efficiency

Chanti¹,

Youzhen²

2019

Discrete &Amp; Continuous Dynamical Systems - S

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A series of phenomena including lower circulation efficiency of Chinese fresh agricultural products, postharvest decay, damage and waste of agricultural products, regional and structural contradiction of supply and demand, drastic fluctuation in price and difficulty in buying and selling, etc. are serious, which has restricted the sound development of Chinese fresh agricultural product industry. To analyze and discuss main factors affecting circulation efficiency of Gannan navel orange, the methods, such as AHP (analytic hierarchy process) and Delphic method, etc., have been used for empirical analysis on Gannan navel orange, and it is found that fruit factors (including single structure and centralized mature period of navel orange, etc), infrastructure factors (including the lack standardization for construction of trading place, outdated warehousing facility and technology, insufficient input of infrastructure of cold chain, etc) and policy environment factors (including food safety, absence of relevant laws and regulations of market supervision, etc) are the existing main factors restricting high-efficient circulation of Gannan navel orange. Based on the conclusion of empirical research and beginning with main circulation links of production, storage and transportation as well as marketing, etc and supporting measures of brand building, product safety and policy service system, etc, the countermeasures and suggestions are proposed to improve circulation efficiency of Gannan navel orange.

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“…The case study is carried out for turbine engine manufacturer, which is in our context the entity that needs production monitoring for laser cutting machines used in production. In related work [21] of the H2020 ICP4Life project, the objectives were concerned with co-designing and specifying the machine components and design according to the user's (turbine engine manufacturer) requirements. However, in the scope of the paper context, the objective is to utilize sensors added to the machine and to ensure data unification, to facilitate and enable data exchange with the service provider.…”

Section: Case Studymentioning

confidence: 99%

Efficient Production Monitoring on the Basis of Domain Ontologies by Utilizing IoT

Riad

Elgammal

Elzanfaly

2019

Communication Papers of the 2019 Federated Conference on Computer Science and Information Systems

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The Internet-of-Things (IoT) technologies and cyber-physical systems has facilitated production monitoring and control. However, researches and applications still lack a standardized framework and an integrated technological solution that can maximize the leverage of real-time monitoring. This can be achieved through enabling data transfer and exchange between all entities/organizations in supply chains and accordingly utilizing the monitored data. This paper introduces a framework for production monitoring that utilizes and integrates ontological model, which implements and integrates Semantic Sensor Network (SSN) ontology with production monitoring services. In addition, Complex Event Processing is integrated in the proposed model to enable event patterns identification and undertake the appropriate (proactive) action accordingly. The framework is constructed based on ISA-95 and SCOR standards. The utility, applicability and efficacy of the proposed framework is validated by its application on a real-life large-scale case study in the domain of laser cutting machines.

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Mitigating risks of perishable products in the cyber-physical systems based on the extended MRP model

Cited by 78 publications

References 49 publications

Internet of things and supply chain management: a literature review

Internet of things and supply chain management: a literature review

A nonlinear empirical analysis on influence factor of circulation efficiency

Efficient Production Monitoring on the Basis of Domain Ontologies by Utilizing IoT

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