Johan Wenngren, Martin Lundgren, Åsa Ericson, Johan Lugnet
The following topics are dealt with: production engineering computing; industrial robots; industrial manipulators; robot programming; computerised numerical control; control engineering computing; intelligent robots; human-robot interaction; factory automation; maximum power point trackers.
<p style='text-indent:20px;'>Manufacturers often face capital constraints when opening up online channel, at this time external financing and internal financing are usually considered. Previous literature has shown that internal financing, turns out to be a better option. To figure out how trade credit financing discount contract affects operations and performances of supply chain, this paper studies the pricing decision of a retailer-dominant dual-channel supply chain with manufacturer's capital constraints. The Stackelberg game models under centralized decision and decentralized decision are constructed. Moreover, this paper conducts research about the effects of revenue-sharing (RS) contract, direct channel price discount (DP) contract and retail channel price discount (RP) contract on the performance of supply chain. Numerical examples are provided to explore the comparison of the optimal pricing strategies and total profits under different contracts. The results show that the retailer prefers RS and DP contracts to RP contract. Among them, RS contract has a broader scope of coordination, while DP contract can achieve a higher profit. The results can serve as insights for decision-makers to choose the most appropriate financial discount contract.
Blockchain has the potential to change business transactions to a major extent. Thereby, underlying consensus algorithms are the core mechanism to achieve consistency in distributed infrastructures. Their application aims for transparency and accountability in societal transactions. As a result of missing reviews holistically covering consensus algorithms, we aim to (1) identify prevalent consensus algorithms for public blockchains, and (2) address the resource perspective with a sustainability consideration, whereby we address the three spheres of sustainability. Our systematic literature review identified 33 different consensus algorithms for public blockchains. Our contribution is twofold: first, we provide a systematic summary of consensus algorithms for public blockchains derived from the scientific literature as well as real-world applications and systematize them according to their research focus; second, we assess the sustainability of consensus algorithms using a representative sample and thereby highlight the gaps in literature to address the holistic sustainability of consensus algorithms.
Scheduling and Optimization Algorithms
Advanced Research in Systems and Signal Processing
Conventional railway operations employ specialized software and hardware to ensure safe and secure train operations. Track occupation and signaling are governed by central control offices, while trains (and their drivers) receive instructions. To make this setup more dynamic, the train operations can be decentralized by enabling the trains to find routes and make decisions which are safeguarded and protocolled in an auditable manner. In this paper, we present the case study findings of a first-of-its-kind blockchain-based prototype implementation for railway control, based on decentralization but also ensuring that the overall system state remains conflict-free and safe. We also show how a blockchain-based approach simplifies usage billing and enables a train-to-train/machine-to-machine economy. Finally, first ideas addressing the use of blockchain technology as a life-cycle approach for condition-based monitoring and predictive maintenance in train operations are outlined.
Conventional railway operations employ specialized software and hardware to\nensure safe and secure train operations. Track occupation and signaling are\ngoverned by central control offices, while trains (and their drivers) receive\ninstructions. To make this setup more dynamic, the train operations can be\ndecentralized by enabling the trains to find routes and make decisions which\nare safeguarded and protocolled in an auditable manner. In this paper, we\npresent the findings of a first-of-its-kind blockchain-based prototype\nimplementation for railway control, based on decentralization but also ensuring\nthat the overall system state remains conflict-free and safe. We also show how\na blockchain-based approach simplifies usage billing and enables a\ntrain-to-train/machine-to-machine economy. Finally, first ideas addressing the\nuse of blockchain as a life-cycle approach for condition based monitoring and\npredictive maintenance in train operations are outlined.\n
Paul Griffin, Alan Megargel, Venky R. Shankararaman
A typical example of a distributed process is trade finance where data and documents are transferred between multiple companies including importers, exporters, carriers, and banks. Blockchain is seen as a potential decentralized technology that can be used to automate such processes. However, there are also other competing technologies such as managed file transfers, messaging, and WebAPIs that may also be suitable for automating similar distributed processes. In this chapter, a decision framework is proposed to assist the solution architect in deciding the technology best suited to support decentralized control of a distributed business process where there are multiple companies involved. The framework takes as input the different areas of concern such as data, processing, governance, technical, and the pros and cons of the technologies in addressing these areas of concerns and provides a method to analyze and highlight the best technology for any process in question. Two example processes, trade finance and price distribution, are used to show the application of the framework.
The persistent development towards decreasing batch sizes due to an ongoing product individualization, as well as increasingly dynamic market and competitive conditions lead to new changeability requirements in production environments. Since each of the individualized products might require different base materials or components and manufacturing resources, the paths of the products going through the factory as well as the required internal transport and material supply processes are going to differ for every product. Conventional planning and control systems, which rely on predefined processes and central decision-making, are not capable to deal with the arising system’s complexity along the dimensions of changing goods, layouts and throughput requirements. The concepts of “self-organization” in combination with “autonomous control” provide promising solutions to solve these new requirements by using among other things the potential of autonomous, decentralized and target-optimized decision-making. A major enabler for the development towards autonomous changeable intralogistics systems are intelligent logistical objects (e.g. smart products, bins and conveyor systems) which are able to communicate and interact with each other as well as with human workers. To investigate the potential of automation and human-robot collaboration for intralogistics, a research project for the development of a collaborative tugger train has been started at the ESB Logistics Learning Factory in line with various student projects in neighboring research areas. This collaborative tugger train system in combination with other manual (e.g. handcarts) and (semi-)automated conveyor systems (e.g. automated guided forklift) will be integrated into a dynamic, self-organized scenario with varying production batch sizes to develop a method for target-oriented self-organization and autonomous control of intralogistics systems. For a structured investigation of self-organized scenarios a generic intralogistics model as well as a criteria catalogue has been developed. The ESB Logistics Learning will serve as a practice-oriented research, validation and demonstration environment for these purposes.
José Barbosa, Paulo Leitão, Adriano Ferreira, Jonas Queiroz · 6 authors
This paper describes the development of a multiagent system (MAS) to support the implementation of zero-defect manufacturing strategies in multi-stage production systems. The MAS infrastructure, combined with on-line inspection tools, data analytics and knowledge generation, constitutes a suitable approach to integrate process and quality control in multi-stage environments. This will allow the early detection of product defects, the adaptation to operating condition changes and the optimisation of manufacturing processes. This type of integrated management structure is aligned with a zero-defect manufacturing production model which is of paramount importance in the actual state-of-the-art manufacturing paradigms. As a proof of concept, the devised manufacturing supervision model was deployed into an experimental multi-stage system that run a set of several tests on electrical motors. The agent-based solution was implemented using the JADE framework and the exchange of information structured by proper data models and industrial based Internet-of-Things and Machine-to-Machine technologies, such as OPC-UA, REST and JSON. The obtained results demonstrate the suitability of the devised integrated management model as a vehicle to achieve dynamic and continuous system improvement in multi-stage manufacturing environments.
Christoph Berger, Urs Hoffmann, Stefan Braunreuther, Gunther Reinhart
Regarding the changing market environment in terms of logic requirements, production planning and control recently contribute significantly to fulfilling these demands. Logistic command variables, particularly adherence to schedule, are becoming the crucial parameters to satisfy the customer's needs. Cyber-Physical production Systems (CPPS) with their characteristics decentralized organization, autonomous control, real-time capability and smart data processing offer new possibilities of production monitoring and control. For this purpose, this paper proposes a new event-based approach in order to improve adherence to schedule in production by using the potential of CPPS. Control loops close to production shop floor provide a fast identification of events. Based on an activity list, the production control is able to react adequately to the different events e.g. machine disturbance or urgent orders. The activities initiated by the Manufacturing Execution System (MES) affect the whole production system while the production. In a final step, the developed concept of an event-driven production control was implement in a simulation.
Blockchain is a form of distributed ledger technology (DLT) that has grown in prominence, although its full potential and possible downsides are not yet fully understood, especially with respect to Operations Management (OM). This manuscript contributes to filling in this gap. We identify three research themes in applying Blockchain technology to OM, illustrated through several applications to OM problems. Elsewhere, in a companion article, (Babich and Hilary (2018)), we provide a conceptual framework for the role of Blockchain and other DLT in OM, along with specific examples of research questions, and we demonstrate how research in economics can inform research in OM on Blockchain applications. Finally, we discuss possible future uses for the technology.
For any industry or company, to be a competent in market needs increase in performance in all possible ways. Quick response to market and sufficient production as per requirement is the only way to increase the returns, which require critical planning and production systems. For this co-ordination between business units or workstations is essential. Many of the executive managers in industries has to instruct only the task flows to its subordinates, that is a single straightforward production planning process is followed as executed from top level of organization; their capacity as per their education level is not utilized more than 10%. The use of multi-agent system allows physical distribution of the decisional system and procures a hierarchical organization structure with decentralized control that guarantees the autonomy of each entity and flexibility of network. Our study focuses on managers/partners that adapt together their local planning process to face different requirements of supply chain environment using different planning strategies, when decisions are supported by distributed planning systems. The agent based system has the advantage of making collaborative management of disturbances in supply chain as the agents has the advantage of making autonomous decisions in a distributed network. Because each partner can choose different behavior and all behavior has an impact on the overall performance, it is difficult to know which is preferable for each partner to increase their performance. Thus, in this paper study of Multi-behavior planning agent model is done using different planning strategies when decisions are supported by distributed planning system.
The innovation of supply chain financial services can alleviate the plight of SMEs financing difficulties. In the aspect of supply chain finance model, there is a credit guarantee financing model, which is different from the simple external financing and internal financing mode of supply chain. Based on this, this paper studies the decision-making of supply chain finance under the partial credit guarantee of core enterprises. First of all, the paper constructs a simple supply chain financing model, consisting of a bank, a core enterprise and a retailer. And then, considering the credit guarantee financing model, calculate the expected profit function. Stackelberg game model is used to give the optimal decision of each subject in decentralized system and the optimal decision in centralized system. Finally, in order to make a more specific and detailed study on the profit and decision-making based on the credit guarantee financing model, the important parameters of the model are analyzed. Through the calculation, it is proved that under the credit guarantee of the core enterprise, the retailer has the optimal ordering strategy, and the core enterprise has the best wholesale price. The influences of the partial credit guarantee coefficient and the retailer’s loan coefficient on the supply chain finance decision-making are also studied.
Future factory production and assembly environments require smart automation and are controlled by a massively increasing number of computers with sensorial feedback from machines, parts, products, and humans, consisting of a wide variety of different networked devices and software programs, which can be considered as one big use case of pervasive and cloud computing with vanishing boundaries between the computing and the environment, and with a strong focus on decentralized distributed computing and information storage. These new complex information processing architectures are composed of hierarchical network graphs, and require some kind of self-organization and adaptability to overcome single-point of failure and robustness constraints. The data acquired from machines and sensitive products or parts are growing at a fast rate, leading to a large data volume that must be handled distributed with pre-processing, map- and reduce, and filtering algorithms. Mobile Agents can be deployed in such large-scale and hierarchical network environments crossing barriers transparently, for example, industrial manufacturing and assembly environments, the Internet, Sensor Networks, and Cyber-Physical Systems. The networks can consist of high- and low-resource nodes ranging from generic computers to microchips, and the supported network classes range from body area networks to the Internet including any kind of sensor and ambient network. Mobile Agents can perform distributed computation in an autonomous manner.In this work Agents are represented by mobile program code that can be modified at run-time by the Agents themselves. The presented approach enables the development of sensor clouds and smart systems of the future integrated in daily use computing environments and the Internet. Agents can migrate between different hardware and software platforms by migrating the program code of the agent, which embeds the control state and the private data of an agent, finally encapsulated in self-initializing and self-containing code frames.This cross-platform interoperability is ensured by a modular and scalable Agent Processing Platform. The entire information exchange and co-ordination of Agents with other Agents and the environment is performed by using a Tuple Space database, unifying the platform and architecture specific data representation. The Tuple Space is used for any kind of information exchange including program code and directory and file system services mapped on the Tuple Space. Beside architecture specific hardware and software implementations of the agent processing platform, there is a JavaScript (JS) implementation layered on the top of a distributed co-ordination and management layer including distributed file and name services. The JS platform enables the integration of Multi-Agent Systems (MAS) in Internet server and application environments (e.g., WEB browser). Agents can migrate transparently between different classes of computing devices and environments, ranging from hardware-level sensor networks (embedded in technical structures) to WEB browser applications or network servers without any required transformation.
Muhammad Hafidz Fazli Md Fauadi, Fairul Azni Jafar, Adi Saptari, Wan Ling Li
The increasingly challenging and dynamic nature of manufacturing industry has driven organizations to enhance their system efficiency. One of the most important aspects in manufacturing plant is the Material Transportation System (MTS). In order to address dynamic factors, MTS need to be equipped with rescheduling capability. This paper focuses on reactive transportation task assignment to a fleet of autonomous Automated Guided Vehicles (AGVs). This paper proposes a Mixed Integer Programming method to reschedule transportation tasks for a non-disruptive job shop manufacturing system based on Multi Agent System (MAS) architecture. The result shows that proposed rescheduling method is able to outperform conventional method significantly.