Mohammad Givehchi

An enriched machining feature based approach to cutting tool selection

ABSTRACT Cutting tools, considered as a basic prerequisite machining resource, are generally selected according to the selected machining methods, which cannot fit in the current manufacturing environment where small- and medium-sized enterprises (SMEs) are the major manufacturers. For the survival of SMEs, it is critical to develop methods for selecting proper cutting tools and reducing machining cost according to product data. Therefore, this study proposes an enriched machining feature (MF)-based approach towards adaptive cutting tool and machining method selection, in which both machinability and machining cost of MF are considered. It includes a two-step workflow: filtering and optimisation. In the filtering process, cutting tools are filtered according to workpiece materials, geometries of MFs and cutting tool inventory, respectively. Here, MF geometries depend on Machining Limit Value decided by sizes and interference relationships of MFs. Also, the client is suggested to choose proper new cutting tools. In the optimisation process, the filtered cutting tools are considered for all the MFs, and machining costs are calculated for each option, in order to select the cheapest one. In particular, if similar cutting tools are required for different MFs, the cutting tool selection for these MFs should be performed altogether.

Knowledge-based Operation Planning and Machine Control by Function Blocks in Web-DPP

Today, the dynamic market requires manufacturing firms to possess high degree of adaptability and flexibility to deal with shop-floor uncertainties. Specifically, targeting SMEs active in the machining and metal cutting sector who normally deal with complex and intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Web-DPP elaborates a two-layer distributed adaptive process planning system based on function-block technology. Function-block enabled machine controllers are one of the elements of this system. In addition, intensive reasoning based on the features data of the products models, machining knowledge, and resource data is needed to be performed inside the function blocks in machine controller side. This paper reports the current state of design and implementation of a knowledge-based operation planning module using a rule-engine embedded in machining feature function blocks, and also the design and implementation of a common interface (for CNC milling machine controller and its specific implementation for a specific commercial controller) embedded in the machining feature function blocks for controlling the machine. The developed prototype is validated through a case-study.

Web based monitoring and control of distant Robotic Operations

In order to improve the production efficiency while facing today’s manufacturing uncertainty, responsive and adaptive capabilities for rapid production changes are essential. This paper presents ho ...

Knowledge-Based Production Planning Within the Reference Planning Process Supporting Manufacturing Change Management

The manufacturing of a product takes place in several partial steps and these mostly in different locations to save tax or to use the best providers. Therefore, in the era of Internet of Things (Io ...

ICMS: A Cloud-Based System for Production Management

Modern production industry calls for a new generation of production systems. As a novel information technology, Cloud provides new service models and business opportunities to manufacturing industry. In this research, a Cloud-based manufacturing system is developed to support distributed production management. Recent Cloud manufacturing approaches are reviewed. The Cloud-based production management and localisation mechanisms are proposed and evaluated during case study. It is shown that the Cloud-based manufacturing system is capable of supporting distributed and customised production services and managements.

Concept for Function Block Enabled Process Planning Towards Multi-Site Cloud Collaboration

In global enterprises an essential challenge is how to enable efficient sharing of knowledge, capacity, and resources in order to meet demands on speed, flexibility and adaptability. This paper highlights challenges and aspects regarding framework and technical platform for process planning that enable global multi-site collaboration. To get an industrial perspective, this topic is discussed in the context of Sandvik Coromants globally distributed application centers. Further on, function block technology as enabling technology to achieve flexible and adaptable process planning as a part of the framework is presented and discussed together with results from the on-going research work.