Artificial Intelligence in Business Processes

2022 ◽  
pp. 205-230
Author(s):  
S. Asif Basit
Keyword(s):  
Neural Networks ◽  
Process Management ◽  
Business Processes ◽  
Control Process ◽  
Shop Floor ◽  
Business Environments ◽  
Novel Approach ◽  
Governing Factor ◽  
Artificial Neurons ◽  
Process Interaction

The aim of this chapter is to establish that the principles used by neural networks can be applied to business process management. The similarity between artificial neurons and business processes, and hence between neural networks and process landscapes, will be demonstrated. This novel approach leads to an emphasis on process interactions and their effect on actions as a major governing factor in controlling process outputs. Stigmergic interaction in biological systems is explored in the context of business processes, and its potential to understand process interaction is investigated. In order to verify the use of stigmergy in business environments, a pilot study is described in which shop floor business processes in a retailing environment are observed and described using a stigmergic framework. Establishing the viability of using stigmergic interaction to control process actions and outputs is the first step towards designing neural process networks.

scholarly journals Exploring potentials of digital nudging for business processes

2020 ◽  
Vol 26 (6) ◽  
pp. 1329-1347
Author(s):  
Sandra Bammert ◽  
Ulrich Matthias König ◽  
Maximilian Roeglinger ◽  
Tabitha Wruck
Keyword(s):  
Process Improvement ◽  
Business Process ◽  
Process Management ◽  
Business Processes ◽  
Future Research ◽  
Content Type ◽  
Process Improvements ◽  
Business Environments ◽  
Digital Nudging ◽  
Agile Process

PurposeBusiness process improvement is vital for organizations as business environments are becoming ever more volatile, uncertain, complex and ambiguous. Process improvement methods help organizations sustain competitiveness. Many existing methods, however, do not fit emerging business environments as they entail initiatives with long implementation times, high investments and limited involvement of process participants. What is needed are agile process improvement approaches. The purpose of this paper is to explore the potential of digital nudging – a concept offering tools that lead individuals to better decisions – to improve business processes.Design/methodology/approachUsing process deviance as theoretical lens, an online experiment with 473 participants is conducted. Within the experiment, business processes and digital nudges are implemented to examine whether digital nudging can mitigate the weaknesses of existing process improvement methods.FindingsDigital nudging can influence the decisions of process participants and entail positive process deviance that leads to process improvement opportunities. Further, the research gives a first hint on the effectiveness of different digital nudges and lays the foundation for future research.Research limitations/implicationsSince exploring a completely new field of research and conducting the experiment in a synthetic environment, the paper serves as a first step toward the combination of digital nudging, business process improvements and positive process deviance.Originality/valueThe major achievement reported in this paper is the exploration of a new field of research. Thus, digital nudging shapes up as a promising foundation for agile process improvement, a discovery calling for future research at the intersection of digital nudging and business process management.

Extending Database Support for Coordination Among Agents

1997 ◽  
Vol 06 (03n04) ◽  
pp. 315-339 ◽  
Author(s):  
Mikael Berndtsson ◽  
Sharma Chakravarthy ◽  
Brian Lings
Keyword(s):  
Problem Solving ◽  
Speech Acts ◽  
Process Management ◽  
Business Processes ◽  
Active Databases ◽  
Levels Of Abstraction ◽  
Cooperative Problem Solving ◽  
Novel Approach ◽  
High Level ◽  
Coordination And Collaboration

Coordination and collaboration are naturally used by groups for carrying out activities and solving problems that require cooperation. However, getting a set of computer agents to do the same has been a problem – primarily addressed by the AI community and recently by the database community as workflow and process management problems (for example, in business processes, electronic commerce, logistics). Not surprisingly, the problem has been addressed at different levels of abstraction by the two communities. Coordination protocols as well as task and result sharing have been investigated by the AI community; specification of alternative transaction models to meet the requirements of non-traditional applications, and their execution have been addressed by the database community. It is evident that there is a need for bringing the two approaches together to develop systems that support cooperative problem solving. This paper – argues for the use of active databases in general and active capability in particular as an enabling technology for cooperative problem solving and cooperative information systems – details a novel approach for supporting task sharing, a key aspect of CPS, using active capability – elaborates on a methodology for mapping task shared protocols expressed in high level speech acts to Event Condition-Action (ECA) rules.

Applying Service-Oriented Composition Process in TPMS

2013 ◽  
Vol 680 ◽  
pp. 526-533
Author(s):  
Cheng Wei Yang ◽  
Lei Wu ◽  
Shi Jun Liu ◽  
Xiang Xu Meng
Keyword(s):  
Management System ◽  
Process Management ◽  
Business Processes ◽  
Previous Method ◽  
It Systems ◽  
Novel Approach ◽  
Service Oriented ◽  
Composition Process ◽  
Integrated Problems

Nowadays, the companies must adapt their business processes changing more dynamically in accordance with rapidly changing market conditions and IT systems. This paper extends our previous method, which shows a novel approach to integrate a service system. In this paper, we focus on the integrated problems of the Business Process Management System (BPMS). The service is encapsulated as a SCA service component，which is extended to be a service surrogate. Meanwhile, the XML-based process template is used to define the composition process. An interactive access control strategy based on service components is also proposed. At the end of this paper, it is applied in the textile-order process management system (TPMS) as a case study.

scholarly journals Managing business processes using soft computing techniques – a literature review

2017 ◽  
Vol 23 (1) ◽  
pp. 63 ◽  
Author(s):  
Nikola D. Vojtek
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Process Management ◽  
Business Processes ◽  
External Factors ◽  
Business Operations ◽  
Soft Computing Techniques ◽  
Internal And External Factors ◽  
And Behavior

Non-ideal and turbulent environment is affecting the business operations of today's companies. The influence and behavior of external factors is not possible or very difficult to predict, but necessary to consider in the decision making process at all organizational levels. Development of computer technologies allowed companies processing large amounts of data in order to make decisions which take into account both internal and external factors. Due to their tolerance of imprecision and uncertainty, Soft computing techniques (SCT) are increasingly used in solving those problems. They are characterized by the ability to adapt quickly to the changes in the environment, stability when processing large amounts of inaccurate data and real time responsiveness. The basic and most commonly used Soft Computing techniques are Fuzzy logic (FL) and neural networks (NN). This paper gives a review of 78 papers referring to the development of theory and practical application of soft computing techniques in business process management. Papers were selected based on the journals impact factor and year of publication (with the focus on recent papers). Approximately, equal number of both Fuzzy logic and Neural Network techniques was tried to be captured. Although this review is not final, it can be considered as a valid guide to explore the opportunities and possibilities which fuzzy logic and neural networks offer process owners in managing their business processes. In conclusion of this paper, fields for further research have been identified.

scholarly journals Automated Generation of a Digital Twin of a Manufacturing System by Using Scan and Convolutional Neural Networks

2020 ◽  
Author(s):  
Markus Sommer ◽  
Josip Stjepandić ◽  
Sebastian Stobrawa ◽  
Moritz von Soden
Keyword(s):  
Neural Networks ◽  
Object Recognition ◽  
Convolutional Neural Networks ◽  
Shop Floor ◽  
Process Chain ◽  
Automated Generation ◽  
Entire Process ◽  
Digital Twin ◽  
Production Processes ◽  
Novel Approach

The simulation of production processes using a Digital Twin is a promising means for prospective planning, analysis of existing systems or process-parallel monitoring. However, many companies, especially small and medium-sized enterprises, do not apply the technology, because the generation of a Digital Twin is cost-, time- and resource-intensive and IT expertise is required. This obstacle can be removed by a novel approach to generate a Digital Twin using fast scans of the shop floor and subsequent object recognition in the point cloud. We describe how parameters and data should be acquired in order to generate a Digital Twin automatically. An overview of the entire process chain is given. A particular attention is given to the automatic object recognition and its integration into Digital Twin.

A Novel Approach for Image Super Resolution Problems with Convolution Neural Networks

2017 ◽  
Vol 6 (4) ◽  
pp. 15
Author(s):  
JANARDHAN CHIDADALA ◽  
RAMANAIAH K.V. ◽  
BABULU K ◽  
◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Super Resolution ◽  
Convolution Neural Networks ◽  
Novel Approach ◽  
Image Super Resolution

scholarly journals Resource Controllability of Business Processes Under Conditional Uncertainty

2021 ◽  
Author(s):  
Matteo Zavatteri ◽  
Carlo Combi ◽  
Luca Viganò
Keyword(s):  
Access Control ◽  
Business Process ◽  
Process Management ◽  
Business Processes ◽  
Autonomous Systems ◽  
Research Problem ◽  
Current Research Problem ◽  
Constraint Networks ◽  
Process Engine ◽  
A Current

AbstractA current research problem in the area of business process management deals with the specification and checking of constraints on resources (e.g., users, agents, autonomous systems, etc.) allowed to be committed for the execution of specific tasks. Indeed, in many real-world situations, role assignments are not enough to assign tasks to the suitable resources. It could be the case that further requirements need to be specified and satisfied. As an example, one would like to avoid that employees that are relatives are assigned to a set of critical tasks in the same process in order to prevent fraud. The formal specification of a business process and its related access control constraints is obtained through a decoration of a classic business process with roles, users, and constraints on their commitment. As a result, such a process specifies a set of tasks that need to be executed by authorized users with respect to some partial order in a way that all authorization constraints are satisfied. Controllability refers in this case to the capability of executing the process satisfying all these constraints, even when some process components, e.g., gateway conditions, can only be observed, but not decided, by the process engine responsible of the execution. In this paper, we propose conditional constraint networks with decisions (CCNDs) as a model to encode business processes that involve access control and conditional branches that may be both controllable and uncontrollable. We define weak, strong, and dynamic controllability of CCNDs as two-player games, classify their computational complexity, and discuss strategy synthesis algorithms. We provide an encoding from the business processes we consider here into CCNDs to exploit off-the-shelf their strategy synthesis algorithms. We introduce $$\textsc {Zeta}$$ Z E T A , a tool for checking controllability of CCNDs, synthesizing execution strategies, and executing controllable CCNDs, by also supporting user interactivity. We use $$\textsc {Zeta}$$ Z E T A to compare with the previous research, provide a new experimental evaluation for CCNDs, and discuss limitations.

scholarly journals Autonomous flight cycles and extreme landings of airliners beyond the current limits and capabilities using artificial neural networks

2021 ◽  
Author(s):  
Haitham Baomar ◽  
Peter J. Bentley
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Training Data ◽  
Aviation Industry ◽  
Control Models ◽  
Novel Approach ◽  
Network Modules ◽  
Artificial Neural

AbstractWe describe the Intelligent Autopilot System (IAS), a fully autonomous autopilot capable of piloting large jets such as airliners by learning from experienced human pilots using Artificial Neural Networks. The IAS is capable of autonomously executing the required piloting tasks and handling the different flight phases to fly an aircraft from one airport to another including takeoff, climb, cruise, navigate, descent, approach, and land in simulation. In addition, the IAS is capable of autonomously landing large jets in the presence of extreme weather conditions including severe crosswind, gust, wind shear, and turbulence. The IAS is a potential solution to the limitations and robustness problems of modern autopilots such as the inability to execute complete flights, the inability to handle extreme weather conditions especially during approach and landing where the aircraft’s speed is relatively low, and the uncertainty factor is high, and the pilots shortage problem compared to the increasing aircraft demand. In this paper, we present the work done by collaborating with the aviation industry to provide training data for the IAS to learn from. The training data is used by Artificial Neural Networks to generate control models automatically. The control models imitate the skills of the human pilot when executing all the piloting tasks required to pilot an aircraft between two airports. In addition, we introduce new ANNs trained to control the aircraft’s elevators, elevators’ trim, throttle, flaps, and new ailerons and rudder ANNs to counter the effects of extreme weather conditions and land safely. Experiments show that small datasets containing single demonstrations are sufficient to train the IAS and achieve excellent performance by using clearly separable and traceable neural network modules which eliminate the black-box problem of large Artificial Intelligence methods such as Deep Learning. In addition, experiments show that the IAS can handle landing in extreme weather conditions beyond the capabilities of modern autopilots and even experienced human pilots. The proposed IAS is a novel approach towards achieving full control autonomy of large jets using ANN models that match the skills and abilities of experienced human pilots and beyond.

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