What are features? An ontology-based review of the literature

Sanfilippo, Emilio M.; Borgo, Stefano

doi:10.1016/j.cad.2016.07.001

Cited by 61 publications

(35 citation statements)

References 89 publications

(115 reference statements)

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“…El Kadiri and Kiritsis [27] reviewed the use of ontologies for product lifecycle management. Sanfilippo and Borgo [32] presented a state of the art of the feature-based product modeling approach and proposed a high-level ontology-based perspective to harmonize the feature definitions. Later, Sanfilippo [33] suggested a modular ontological architecture and a general framework where features are contextualized within a larger system for product knowledge representation.…”

Section: Semantic Web Technologies For Mps According Tomentioning

confidence: 99%

An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection

Mabkhot

Al-Samhan

Hidri

2019

Advances in Materials Science and Engineering

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In nowadays industry 4.0 and changeable manufacturing context, designers and manufacturing engineers struggle to determine appropriate quick, accurate (with flawless quality), and cost-effective processes to design highly customized products to meet customer requirements. To determine manufacturing processes, the matching between product features, material characteristics, and process capabilities needs to be optimized. Finding such an optimized matching is usually referred to as manufacturing process selection (MPS), which is not an easy task because of the infinite combinations of product features, numerous material characteristics, and various manufacturing processes. Although problems associated with MPS have received considerable attention, semantic web technologies are still underexplored and their potential is still uncovered. Almost no previous study has considered combining case-based reasoning (CBR) with ontologies, a famous and powerful semantic web enabler, to achieve MPS. In this study, we developed a decision support system (DSS) for MPS based on ontology-enabled CBR. By applying automatic reasoning and similarity retrieving on an industrial case study, we show that ontologies enable process selection by determining competitive matching between product features, material characteristics, and process capabilities and by endorsing effective case retrieval.

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Section: Semantic Web Technologies For Mps According Tomentioning

confidence: 99%

An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection

Mabkhot

Al-Samhan

Hidri

2019

Advances in Materials Science and Engineering

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“…Feature technology represents an essential tool for computer integrated manufacturing (CIM), which is considered a focal research area in manufacturing industry. The main two approaches in this field are design by features (DBF) and automated feature recognition [30][31][32][33][34].…”

Section: Feature Technologymentioning

confidence: 99%

A survey on smart automated computer-aided process planning (ACAPP) techniques

Al-wswasi

Ivanov

Makatsoris

2018

Int J Adv Manuf Technol

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The concept of smart manufacturing has become an important issue in the manufacturing industry since the start of the twenty-first century in terms of time and production cost. In addition to high production quality, a quick response could determine the success or failure of many companies and factories. One the most effective concepts for achieving a smart manufacturing industry is the use of computer-aided process planning (CAPP) techniques. Computer-aided process planning refers to key technology that connects the computer-aided design (CAD) and the computer-aided manufacturing (CAM) processes. Researchers have used many approaches as an interface between CAD and CAPP systems. In this field of research, a lot of effort has been spent to take CAPP systems to the next level in the form of automatic computer-aided process planning (ACAPP). This is to provide complete information about the product, in a way that is automated, fast, and accurate. Moreover, automatic feature recognition (AFR) techniques are considered one of the most important tasks to create an ACAPP system. This article presents a comprehensive survey about two main aspects: the degree of automation in each required input and expected output of computer-aided process planning systems as well as the benefits and the limitations of the different automatic feature recognition techniques. The aim is to demonstrate the missing aspects in smart ACAPP generation, the limitations of current systems in recognising new features, and justifying the process of selection.

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“…Technically, based on the field of Computer Science, ontology is a logical theory that is normally encoded using knowledge representation languages such as, First Order Logic (FOL), very popular Web Ontology Language (OWL) [9]. Ideally, Ontology is a data modeling technique for structured data repository Representation Systems for various Domains Copyright © 2020 MECS I.J.…”

Section: Introductionmentioning

confidence: 99%

A Review on Ontology Development Methodologies for Developing Ontological Knowledge Representation Systems for various Domains

Aminu¹,

Oyefolahan²,

Abdullahi³

et al. 2020

IJIEEB

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The success of machine represented web known as semantic web largely hinges on ontologies. Ontology is a data modeling technique for structured data repository premised on collection of concepts with their semantic relationships and constraints on domain. There are existing methodologies to aid ontology development process. However, there is no single correct ontology design methodology. Therefore, this paper aims to present a review on existing ontology development approaches for different domains with the goal of identifying individual methodology's weakness and suggests for hybridization in order to strengthen ontology development in terms of its content and constructions correctness. The analysis and comparison of the review were carried out by considering these criteria but not limited to: activities of each method, the initial domain of the methodology, ontology created from scratch or reuse, frequently used ontology management tools based on literature, subject granularity, and usage across different platforms. This review based on the literature showed some approaches that exhibit the required principles of ontology engineering in tandem with software development principles. Nonetheless, the review still noted some gaps among the methodologies that when bridged or hybridized a better correctness of ontology development would be achieved in building intelligent system.

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What are features? An ontology-based review of the literature

Cited by 61 publications

References 89 publications

An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection

An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection

A survey on smart automated computer-aided process planning (ACAPP) techniques

A Review on Ontology Development Methodologies for Developing Ontological Knowledge Representation Systems for various Domains

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