Proposal of a methodology for implementing a service-oriented architecture in distributed manufacturing systems

As envisioned by Intelligent Manufacturing Systems (IMS), Next Generation Manufacturing Systems (NGMS) will satisfy the needs of an increasingly fast-paced and demanding market by dynamically integrating systems from inside and outside the manufacturing firm itself into a so-called extended enterprise. However, organizing these systems to ensure the maximum flexibility and interoperability with those from other organizations is difficult. Additionally, a defect in the system would have a great impact: it would affect not only its owner, but also its partners. For these reasons, we argue that a service-oriented architecture (SOA) would be a good candidate. It should be designed following a methodology where services play a central role, instead of being an implementation detail. In order for the architecture to be reliable enough as a whole, the methodology will need to help find errors before they arise in a production environment. In this paper we propose using SOA-specific testing techniques, compare some of the existing methodologies and outline several extensions upon one of them to integrate testing techniques

Smart Manufacturing and Intelligent Manufacturing:A Comparative Review

The application of intelligence to manufacturing has emerged as a compelling topic for researchers and industries around the world. However, different terminologies, namely smart manufacturing (SM) and intelligent manufacturing (IM), have been applied to what may be broadly characterized as a similar paradigm by some researchers and practitioners. While SM and IM are similar, they are not identical. From an evolutionary perspective, there has been little consideration on whether the definition, thought, connotation, and technical development of the concepts of SM or IM are consistent in the literature. To address this gap, the work performs a qualitative and quantitative investigation of research literature to systematically compare inherent differences of SM and IM and clarify the relationship between SM and IM. A bibliometric analysis of publication sources, annual publication numbers, keyword frequency, and top regions of research and development establishes the scope and trends of the currently presented research. Critical topics discussed include origin, definitions, evolutionary path, and key technologies of SM and IM. The implementation architecture, standards, and national focus are also discussed. In this work, a basis to understand SM and IM is provided, which is increasingly important because the trend to merge both terminologies rises in Industry 4.0 as intelligence is being rapidly applied to modern manufacturing and human–cyber–physical systems

Reference architecture for configuration, planning and control of 21st century manufacturing systems.

Today's dynamic marketplace requires flexible manufacturing systems capable of cost-effective high variety - low volume production in frequently changing product demand and mix. Several new paradigms, e.g. holonic, fractal, biological and responsive manufacturing, have recently been proposed and studied in the academic literature. These 'next generation of manufacturing systems' have been especially designed to meet the requirements of an unstable and unpredictable marketplace. However, very little in-depth research of the configuration, planning and control methodologies of these new concepts has been conducted. This research aims to improve the comprehension and implementation of these 21st century manufacturing systems by developing an integrated reference architecture from the combination of their distinctive features that would enable manufacturing enterprises to handle successfully the configuration/reconfiguration, planning and control activities under the conditions of uncertainty and continuous change.In the course of the research, a detailed investigation into the fractal, biological and responsive manufacturing systems is conducted in order to identify the strengths and weaknesses of each concept. The common and distinctive features of the paradigms are then used to merge them to create an integrated reference architecture. The fractal configuration, biological scheduling and 'resource element' representation of resource capabilities and product processing requirements are selected as the major elements of the new system. A detailed study of fractal layout design resulted in seven distinctive methods for structuring and managing fractal cellular systems. A design methodology that supports three types of dynamic scheduling is developed for biological manufacturing systems. Resource elements are used with fractal layouts and biological scheduling to enhance performance and to enable an integration of the concepts. The proposed reference architecture is modelled and evaluated using object-oriented programming, computer simulation and heuristic algorithms. The research results indicate that the performance of systems that employ biological scheduling and fractal layouts can be improved by using the concept of resource elements to utilise any hidden capabilities of resources and to achieve an optimal distribution of resources on the shop floor

Fractal architecture for 'leagile' networked enterprises.

The manufacturing environment and markets in recent times are becoming increasingly dynamic, diverse and unpredictable, due mainly to fast evolution of products and technology, erratic customer behaviour and high consumerism and an increasingly shorter lead-time. The burden of the impact falls on organisational structures built on centralized, rigid manufacturing architecture, because they cannot cope or adapt to the highly uncertain or unpredictable nature of the market. Enterprises who wish to survive these challenges need to rethink their business and manufacturing models, and most importantly reinvent their tactical, operational and organizational formulas to leverage their strategic long term visions.Newer manufacturing systems to curb the effects of this upheaval have to promote an entirely decentralised, flexible, distributed, configurable and adaptable architecture to ameliorate this condition. Many philosophies are proposed and studied towards planning, monitoring, and controlling the 21st century manufacturing system. These include - Bionic manufacturing system (BMS), Holonic manufacturing system (HMS), Fractal manufacturing system (FrMS), Responsive manufacturing etc.This research program focuses on the FrMS, which has vast conceptual advantageous features among these new philosophies, but its implementation has proved very difficult. FrMS is based on autonomous, cooperating, self-similar agent called fractal that has the capability of perceiving, adapting and evolving with respect to its partners and environment. The fractal manufacturing configuration uses self regulating, organisational work groups, each with identical goals and within its own area of competence to build up an integrated, holistic network system of companies. This network yields constant improvement as well as continuous checks and balances through self-organising control loops. The study investigates and identifies the nature, characteristic features and feasibility of this system in comparison to traditional approaches with a detailed view to maximising the logistical attribute of lean manufacturing system and building a framework for 'leagile' (an integration of lean and agile solutions) networked capabilities. It explores and establishes the structural characteristic potentials of Fractal Manufacturing Partnership (FMP), a hands-on collaboration between enterprises and their key suppliers, where the latter become assemblers of their components while co-owning the enterprise's facility, to create and achieve high level of responsiveness. It is hoped that this architecture will drive and harness the evolution from a vertically integrated company, to a network of integrated, leaner core competencies needed to tackle and weather the storm of the 21st century manufacturing system

Application of ”ART SIMULATOR” for Manufacturing Similarity Identification in Group Technology Design - Chapter 10

This chapter 10 carried out the exceptional implementation of ART-1 neural network in the analysis of the manufacturing similarity of the cylindrical parts within the group technology design. Established concept of the group technology design begins from the complex part of the group or the group representative. Group representative has all the geometrical elements of the parts in group, and manufacturing procedure may be applied to the machining of any part in the group. The complex part may be realistic or a hypothetical one. The ART-1 artificial neural network provided manufacturing classification according to the geometrical similarities of work-pieces for the group of cylindrical parts. For the manufacturing similarity identification within the group technology design, software package "ART Simulator" is developed and presented in this chapter

The BG News December 7, 1998

The BGSU campus student newspaper December 7, 1998. Volume 82 - Issue 69https://scholarworks.bgsu.edu/bg-news/7417/thumbnail.jp

Interconnected Services for Time-Series Data Management in Smart Manufacturing Scenarios

xvii, 218 p.The rise of Smart Manufacturing, together with the strategic initiatives carried out worldwide, have promoted its adoption among manufacturers who are increasingly interested in boosting data-driven applications for different purposes, such as product quality control, predictive maintenance of equipment, etc. However, the adoption of these approaches faces diverse technological challenges with regard to the data-related technologies supporting the manufacturing data life-cycle. The main contributions of this dissertation focus on two specific challenges related to the early stages of the manufacturing data life-cycle: an optimized storage of the massive amounts of data captured during the production processes and an efficient pre-processing of them. The first contribution consists in the design and development of a system that facilitates the pre-processing task of the captured time-series data through an automatized approach that helps in the selection of the most adequate pre-processing techniques to apply to each data type. The second contribution is the design and development of a three-level hierarchical architecture for time-series data storage on cloud environments that helps to manage and reduce the required data storage resources (and consequently its associated costs). Moreover, with regard to the later stages, a thirdcontribution is proposed, that leverages advanced data analytics to build an alarm prediction system that allows to conduct a predictive maintenance of equipment by anticipating the activation of different types of alarms that can be produced on a real Smart Manufacturing scenario

The influence of emotional intelligence on, political behaviour of students

This paper discusses the importance of strengthening emotional intelligence (EI) among youths to achieve more integrated human domains. Human capital resources targeting youths are one of the main thrusts of national development in Malaysia especially from the political, economic, social and educational aspects. The main purpose of this study was to test the presence of and the significance (if any) of the relationship between EI competence and the constructs determining youths’ political behaviour. A total of 313 students from four public universities in Malaysia were selected as the sample. The Emotional Intelligence Self-Description Inventory (EISDI), and Political Behaviour Questionnaire (PBQ) were used to obtain data which was analysed using correlation and regression analysis. The findings showed that the two hypotheses were accepted, i.e. there is a correlation between EI with political behaviour which significantly influenced EI on the constructs of political behaviour namely conservativism and nationalism. Hence, EI can be construed to be a determining factor in behaviour and ideology that signifies political maturity among Malaysian yout

Interconnected Services for Time-Series Data Management in Smart Manufacturing Scenarios

xvii, 218 p.The rise of Smart Manufacturing, together with the strategic initiatives carried out worldwide, have promoted its adoption among manufacturers who are increasingly interested in boosting data-driven applications for different purposes, such as product quality control, predictive maintenance of equipment, etc. However, the adoption of these approaches faces diverse technological challenges with regard to the data-related technologies supporting the manufacturing data life-cycle. The main contributions of this dissertation focus on two specific challenges related to the early stages of the manufacturing data life-cycle: an optimized storage of the massive amounts of data captured during the production processes and an efficient pre-processing of them. The first contribution consists in the design and development of a system that facilitates the pre-processing task of the captured time-series data through an automatized approach that helps in the selection of the most adequate pre-processing techniques to apply to each data type. The second contribution is the design and development of a three-level hierarchical architecture for time-series data storage on cloud environments that helps to manage and reduce the required data storage resources (and consequently its associated costs). Moreover, with regard to the later stages, a thirdcontribution is proposed, that leverages advanced data analytics to build an alarm prediction system that allows to conduct a predictive maintenance of equipment by anticipating the activation of different types of alarms that can be produced on a real Smart Manufacturing scenario