Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information

Requirements elicitation requires extensive knowledge and deep understanding of the problem domain where the final system will be situated. However, in many software development projects, analysts are required to elicit the requirements from an unfamiliar domain, which often causes communication barriers between analysts and stakeholders. In this paper, we propose a requirements ELICitation Aid tool (ELICA) to help analysts better understand the target application domain by dynamic extraction and labeling of requirements-relevant knowledge. To extract the relevant terms, we leverage the flexibility and power of Weighted Finite State Transducers (WFSTs) in dynamic modeling of natural language processing tasks. In addition to the information conveyed through text, ELICA captures and processes non-linguistic information about the intention of speakers such as their confidence level, analytical tone, and emotions. The extracted information is made available to the analysts as a set of labeled snippets with highlighted relevant terms which can also be exported as an artifact of the Requirements Engineering (RE) process. The application and usefulness of ELICA are demonstrated through a case study. This study shows how pre-existing relevant information about the application domain and the information captured during an elicitation meeting, such as the conversation and stakeholders' intentions, can be captured and used to support analysts achieving their tasks.Comment: 2018 IEEE 26th International Requirements Engineering Conference Workshop

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Combination of linear classifiers using score function -- analysis of possible combination strategies

In this work, we addressed the issue of combining linear classifiers using their score functions. The value of the scoring function depends on the distance from the decision boundary. Two score functions have been tested and four different combination strategies were investigated. During the experimental study, the proposed approach was applied to the heterogeneous ensemble and it was compared to two reference methods -- majority voting and model averaging respectively. The comparison was made in terms of seven different quality criteria. The result shows that combination strategies based on simple average, and trimmed average are the best combination strategies of the geometrical combination

A design-for-casting integrated approach based on rapid simulation and modulus criterion

This paper presents a new approach to the design of cast components and their associated tools. The current methodology is analysed through a case study and its main disadvantages underlined. Then, in order to overcome these identified drawbacks, a new approach is proposed. Knowing that this approach is mainly based on a rapid simulation of the process, basics of a simplified physical model of solidification are presented as well as an associated modulus criterion. Finally, technical matters for a software prototype regarding the implementation of this Rapid Simulation Approach (RSA) in a CAD environment are detailed

Expect the unexpected: the co-construction of assistive artifacts

This paper aims to explain emerging design activities within community-based rehabilitation contexts through the science of self-organization and adaptivity. It applies an evolutionary systematic worldview (Heylighen, 2011) to frame spontaneous collaboration between different local agents which produce self-made assistive artifacts. Through a process of distinction creation and distinction destruction occupational therapist, professional non-designers, caregivers and disabled people co-evolve simultaneously towards novel possibilities which embody a contemporary state of fitness. The conversation language is build on the principles of emotional seeding through stigmergic prototyping and have been practically applied as a form of design hacking which blends design time and use time. Within this process of co-construction the thought experiment of Maxwell’s Demon is used to map perceived behavior and steer the selecting process of following user-product adaptation strategies. This practice-based approach is illustrated through a case study and tries to integrate both rationality and intuition within emerging participatory design activities

A vision-based system for inspecting painted slates

Purpose – This paper describes the development of a novel automated vision system used to detect the visual defects on painted slates. Design/methodology/approach – The vision system that has been developed consists of two major components covering the opto-mechanical and algorithmical aspects of the system. The first component addresses issues including the mechanical implementation and interfacing the inspection system with the development of a fast image processing procedure able to identify visual defects present on the slate surface. Findings – The inspection system was developed on 400 slates to determine the threshold settings that give the best trade-off between no false positive triggers and correct defect identification. The developed system was tested on more than 300 fresh slates and the success rate for correct identification of acceptable and defective slates was 99.32 per cent for defect free slates based on 148 samples and 96.91 per cent for defective slates based on 162 samples. Practical implications – The experimental data indicates that automating the inspection of painted slates can be achieved and installation in a factory is a realistic target. Testing the devised inspection system in a factory-type environment was an important part of the development process as this enabled us to develop the mechanical system and the image processing algorithm able to perform slate inspection in an industrial environment. The overall performance of the system indicates that the proposed solution can be considered as a replacement for the existing manual inspection system. Originality/value – The development of a real-time automated system for inspecting painted slates proved to be a difficult task since the slate surface is dark coloured, glossy, has depth profile non-uniformities and is being transported at high speeds on a conveyor. In order to address these issues, the system described in this paper proposed a number of novel solutions including the illumination set-up and the development of multi-component image-processing inspection algorithm

Cork parquet quality control vision system based on texture segmentation and fuzzy grammar

This paper presents a quality control vision system developed for the inspection of cork parquets that is already applied in the Portuguese cork industry. It is devoted specifically to the most critical quality issues: visibility of the lowest layer (BASE) on the noble layer (UPPER) and the homogeneity of this noble layer. Since these aspects are related with the texture of the raw material, the system was based on texture segmentation techniques. Features used were extracted from detail images of the wavelet transform. The classifier consists of a fuzzy grammar inference system. The segmentation procedure revealed a good performance indicated by high classification rates. Behavior in the industrial environment has been demonstrating high performance, revealing good perspectives for full spread industrialization