Reducing food losses and carbon emission by using autonomous control – A simulation study of the intelligent container

Haass, Rasmus; Dittmer, Patrick; Veigt, Marius; Lütjen, Michael

doi:10.1016/j.ijpe.2014.12.013

Cited by 97 publications

(58 citation statements)

References 18 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

958

541

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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

958

541

View full text Add to dashboard Cite

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“…Based on the MLD model (11) and (12), we propose an optimal controller that optimizes the quality of perishable food and its associated energy consumption. Essentially, OC is a control methodology that makes explicit use of a dynamical model to obtain control actions by minimizing an objective over a horizon, taking into account the constraints on states, outputs, and inputs.…”

Section: Optimal Controlmentioning

confidence: 99%

Piecewise affine approximations for quality modeling and control of perishable foods

Xin

Negenborn

Xiang

2017

Optim Control Appl Methods

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Summary This paper proposes a new methodology for modeling and controlling quality degradation of perishable foods when zero‐order kinetics are considered. This methodology approximates the nonlinear model of the zero‐order quality kinetics using the piecewise affine (PWA) modeling representation. For obtaining a proper PWA model, two state‐of‐the‐art methods are discussed, and eventually, a hybrid identification‐based PWA model is considered after the comparison. This PWA model is then transformed into a computational mixed logical dynamical model, based on which an optimal control strategy is proposed that balances food quality and associated energy consumption. Furthermore, a model predictive control is proposed for improving energy efficiency when a dynamical weather environment is considered. Simulation experiments illustrate the potentials of the proposed optimal controller and the model predictive controller in a case study involving the bighead carp.

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“…Regarding warehouse management methods, there are several approaches for goods dispatching (Haass et al, 2015). Regular methods are FIFO (First In First Out), LIFO (Last In First Out) and SIRO (Sequence In Random Out).…”

Section: Literature Reviewmentioning

confidence: 99%