Embedded devices for supply chain applications: Towards hardware integration of disparate technologies

Musa, Ahmed; Gunasekaran, Angappa; Yusuf, Yahaya; Abdelazim, Abdelrahman

doi:10.1016/j.eswa.2013.07.017

Cited by 31 publications

(22 citation statements)

References 97 publications

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“…Whereas many ideas and experiences might be transferable from existing approaches to improve the efficiency and success rate of automation concepts and HCI in production logistics settings, also new insights are required as for example how automation and robotics concepts have to be designed in order to allow for a smooth change management in this specific application field of production logistics and to develop the worker's self-efficacy as outlined in Section 4 [11,17,19,111,112]. This is highly relevant for management practice as there are many projects for further automation steps at the doorsteps in most companies.…”

Section: Practical Implicationsmentioning

confidence: 99%

Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future

Klumpp¹,

Hesenius

Meyer

et al. 2019

Int J Adv Manuf Technol

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Current concept, development, and testing applications in production concerning Cyber-Physical Systems (CPS), Industry 4.0 (I40), and Internet of Things (IoT) are mainly addressing fully autonomous systems, fostered by an increase in available technologies regarding distributed decision-making, sensors, and actuators for robotics systems. This is applied also to production logistics settings with a multitude of transport tasks, e.g., between warehousing or material supply stations and production locations within larger production sites as for example in the automotive industry. In most cases, mixed environments where automated systems and humans collaborate (e.g., cobots) are not in the center of analysis and development endeavors although the worker's adoption and acceptance of new technologies are of crucial relevance. From an interdisciplinary research perspective, this constitutes an important research gap, as the future challenges for successful automated systems will rely mainly on human-computer interaction (HCI) in connection with an efficient collaboration between motivated workers, automated robotics, and transportation systems. We develop a HCI efficiency description in production logistics based on an interdisciplinary analysis consisting of three interdependent parts: (i) a production logistics literature review and process study, (ii) a computer science literature review and simulation study for an existing autonomous traffic control algorithm applicable to production logistics Purpose This paper addresses three approaches determined to analyze the crucial role of human interaction in automated environments in production logistics and Industry 4.0 settings. The methods stem from different disciplines as successful automation concepts also have to consider computer science, economics and work science perspectives. Contribution We answer the question of human intuition and its development within a digitalized production logistics setting as well as automated algorithm reaction to human actions from an interdisciplinary perspective. So far, existing research contributions are mainly focusing on technical aspects and automation concepts as solely computer science optimization aspects. However, feasible and sustainable concepts for automated production, e.g., within production transport will only work out if the human factor is included as for a long time to come production environments will be mixed settings of robotics and human workers. Thus, we develop a HCI efficiency description in production logistics for future research and business applications.

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Section: Practical Implicationsmentioning

confidence: 99%

Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future

Klumpp¹,

Hesenius

Meyer

et al. 2019

Int J Adv Manuf Technol

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“…Studies (Musa et al, 2014;Li and Xiao, 2013;Hogpracha and Vongpradhip, 2015;Qi et al, 2015) have identified several key problems with different logistics architectures in which the most critical are discussed below.…”

Section: Related Workmentioning

confidence: 99%

“…Tracking objects in real time not only requires processing power and storage but also r devices and the techniques for collecting data in real time. To tackle these issues, Musa et al (2014) introduced the concept of embedded devices which process data as a background activity, while others presented the idea of local databases (Li and Xiao, 2013) and warehouses which process their data and send them back to the main server for integration.…”

Section: Issues With Logistics Architecture In Ubiquitous Environmentsmentioning

confidence: 99%

“…Using QR codes, one can find out almost everything about the container as well end user personal information such as name, address, contact number, etc. To prevent unauthorized access to users' personal information, several authors (Musa et al, 2014;Li and Xiao, 2013;Hogpracha and Vongpradhip, 2015;Qi et al, 2015) proposed encryption algorithm, so no unauthorized person obtains private information without having the key.…”

Section: Issues With Logistics Architecture In Ubiquitous Environmentsmentioning

confidence: 99%

See 1 more Smart Citation

Real Time Object Tracking and Protection: Hybrid Logistics Architecture in Ubiquitous Environments (HLAiUE)

Patel¹,

Alsadoon²,

Prasad³

et al. 2018

American Journal of Applied Sciences

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Realtime object security and vehicle tracking have not been successfully implemented in commercial vehicles due to limitations in processing large amount of data and hardware capabilities. This paper aimed to improve the object security, processing power and data storage in a distributed environment. The proposed system (HLAiUE) consists of a threelayer architecture, first layer is used to collect data, second layer distributes the data processing and the last layer stores the processed data. The designed architecture improves the performance and security by applying data compression algorithms in a real time and removes the hardware dependency by processing the data in a distributed environment using Hadoop and Spark framework. The results demonstrate that the proposed architecture improves processing time by 80% compared to other algorithms and provides more reliability, security and flexibility due to ubiquity and the absence of hardware dependency in comparison with other existing architectures which are hardware dependent. Also, using an NOSQL database server in a distributed environment optimizes data storage by up to 80% and is flexible because all the infrastructure is in a distributed environment. The proposed architecture improves the object tracking by implementing compression technique in a distributed architecture. Thus, this system improves the accuracy up to 80% without depending on hardware resources.

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“…In the past, working areas of robots and humans in production and transportation were largely separated and in case of cooperation, for example, in truck driving or CNC manufacturing, the roles were clear: Human workers performed control and decision tasks, machines and robots executed the mechanical tasks of production and transportation. That situation however is changing as automation enters a new stage of AI applications (Wong et al 2012;Musa et al 2014;Zhang et al 2014;Knoll et al 2016;Li et al 2017;Deng 2018). Robots, machines, and devices such as containers or transportation equipment will be able to take informed and advanced decisions without manual intervention, while the human workforce takes a supervisory control and oversight role (Castelfranchi and Falcone 2000;Cantor 2016;Crainic and Montreuil 2016;Phan et al 2017;Zhong et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Logistics Innovation and Social Sustainability: How to Prevent an Artificial Divide in Human–Computer Interaction

Klumpp

Zijm

2019

J of Business Logistics

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Human–computer interaction (HCI) is a cornerstone for the success of technical innovation in the logistics and supply chain sector. As a major part of social sustainability, this interaction is changing as artificial intelligence applications (Internet of Things, autonomous transport, Physical Internet) are implemented, leading to larger machine autonomy, and hence the transition from a primary executive to a supervisory role of human operators. A fundamental question concerns the level of control transferred to machines, such as autonomous vehicles and automatic materials handling devices. Problems include a lack of human trust toward automatic decision making or an inclination to override the system in case automated decisions are misperceived. This paper outlines a theoretical framework, describing different levels of acceptance and trust as a key HCI element of technology innovation, and points to the possible danger of an artificial divide at both the individual and firm level. Based upon the findings of four benchmark cases, a classification of the roles of human employees in adopting innovations is developed. Measures at operational, tactical, and strategic level are discussed to improve HCI, more in particular the capacity of individuals and firms to apply state‐of‐the‐art techniques and to prevent an artificial divide, thereby increasing social sustainability.

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Embedded devices for supply chain applications: Towards hardware integration of disparate technologies

Cited by 31 publications

References 97 publications

Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future

Production logistics and human-computer interaction—state-of-the-art, challenges and requirements for the future

Real Time Object Tracking and Protection: Hybrid Logistics Architecture in Ubiquitous Environments (HLAiUE)

Logistics Innovation and Social Sustainability: How to Prevent an Artificial Divide in Human–Computer Interaction

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