Function Block Design to Enable Adaptive Job Shop Operations

2007 ◽  
Author(s):  
Lihui Wang ◽  
Hsi-Yung Feng ◽  
Changjin Song ◽  
Wei Jin
Keyword(s):  
Job Shop ◽  
Block Design ◽  
Shop Floor ◽  
Manufacturing Companies ◽  
New Approach ◽  
Process Plan ◽  
Function Block ◽  
Job Shop Operations ◽  
Function Blocks ◽  
Block Based

Small volume and high product-mix contribute greatly to the complexity of job shop operations. In addition, shop floor uncertainty or fluctuation is another issue regularly challenging manufacturing companies, including job delay, urgent job insertion, fixture shortage, missing tool, and even machine breakdown. Targeting the uncertainty, we propose a function block based approach to generating adaptive process plans. Enabled by the function blocks, a so-generated process plan is responsive and tolerant to an unpredictable change. This paper presents in detail how a function block is designed and what it can do during process plan execution. It is expected that this new approach can largely enhance the dynamism of fluctuating job shop operations.

Alternative Shop-Floor Re-Layout Design due to Dynamic Operation Changes

2011 ◽  
Author(s):  
Lihui Wang
Keyword(s):  
Material Handling ◽  
Job Shop ◽  
Shop Floor ◽  
Layout Problem ◽  
Dynamic Nature ◽  
Manufacturing Operations ◽  
Job Shop Operations ◽  
Function Blocks ◽  
The Cost ◽  
Dynamic Job Shop

The turbulent environment of dynamic job-shop operations affects shop-floor layout as well as manufacturing operations. Due to the dynamic nature of shop-floor layout changes, essential requirements such as adaptability and responsiveness to the changes need to be considered in addition to the cost issues for material handling and machine relocation when reconfiguring a shop floor’s layout. Here, based on the source of uncertainty, the shop floor layout problem is split into two sub-problems and dealt with by two modules: re-layout and find-route. Genetic algorithm is used where changes may cause a re-layout of the entire shop, while function blocks are utilised to find the best sequence of robots for the new conditions within the existing layout. This paper reports the latest development to the author’s previous work.

Overview of a Distributed Process Planning Approach Targeting Manufacturing Uncertainty

2006 ◽  
Author(s):  
Lihui Wang ◽  
Ningxu Cai ◽  
Hsin-Yung Feng
Keyword(s):  
Process Planning ◽  
Job Shop ◽  
Layer Structure ◽  
Dynamic Decision Making ◽  
Machining Process ◽  
Operation Planning ◽  
Planning Approach ◽  
Job Shop Operations ◽  
Function Blocks ◽  
Distributed Process

This paper presents an overview of our DPP (distributed process planning) approach, covering DPP concept, generic machining process sequencing using enriched machining features, process plan encapsulation in function blocks, and process monitoring enabled by the function blocks. A two-layer structure of Supervisory Planning and Operation Planning is proposed in DPP to separate generic data from machine-specific ones. The supervisory planning is only performed once, in advance, at shop level, whereas the operation planning is carried out at runtime at machine level. This dynamic decision-making is facilitated by a set of resource-driven algorithms embedded in the function blocks. The internal structures of typical function blocks are also introduced in the paper. The DPP approach and algorithms are further verified through a case study before drawing conclusions. It is expected that the new approach can largely enhance the dynamism of fluctuating job shop operations.

Function block design for adaptive execution control of job shop machining operations

2009 ◽  
Vol 47 (12) ◽  
pp. 3413-3434 ◽  
Author(s):  
Lihui Wang ◽  
Hsi-Yung Feng ◽  
Changjin Song ◽  
Wei Jin
Keyword(s):  
Job Shop ◽  
Block Design ◽  
Function Block ◽  
Adaptive Execution ◽  
Machining Operations

Function Block-Based Multimodal Control for Symbiotic Human–Robot Collaborative Assembly

2021 ◽  
Vol 143 (9) ◽  
Author(s):  
Sichao Liu ◽  
Lihui Wang ◽  
Xi Vincent Wang
Keyword(s):  
Robot Control ◽  
Control Approach ◽  
Function Block ◽  
Collaborative Assembly ◽  
Function Blocks ◽  
Feature Based ◽  
Human Operators ◽  
Block Based ◽  
And Control ◽  
Assembly Tasks

AbstractIn human–robot collaborative assembly, robots are often required to dynamically change their preplanned tasks to collaborate with human operators in close proximity. One essential requirement of such an environment is enhanced flexibility and adaptability, as well as reduced effort on the conventional (re)programming of robots, especially for complex assembly tasks. However, the robots used today are controlled by rigid native codes that cannot support efficient human–robot collaboration. To solve such challenges, this article presents a novel function block-enabled multimodal control approach for symbiotic human–robot collaborative assembly. Within the context, event-driven function blocks as reusable functional modules embedded with smart algorithms are used for the encapsulation of assembly feature-based tasks/processes and control commands that are transferred to the controller of robots for execution. Then, multimodal control commands in the form of sensorless haptics, gestures, and voices serve as the inputs of the function blocks to trigger task execution and human-centered robot control within a safe human–robot collaborative environment. Finally, the performed processes of the method are experimentally validated by a case study in an assembly work cell on assisting the operator during the collaborative assembly. This unique combination facilitates programming-free robot control and the implementation of the multimodal symbiotic human–robot collaborative assembly with the enhanced adaptability and flexibility.

Function-Block Enabled Job Shop Planning and Control With Uncertainty

2004 ◽  
Author(s):  
Lihui Wang ◽  
Zhenkai Liu ◽  
Weiming Shen ◽  
Sherman Lang
Keyword(s):  
Process Planning ◽  
Job Shop ◽  
Function Block ◽  
Planning And Control ◽  
Planning Approach ◽  
Job Shop Operations ◽  
Batch Sizes ◽  
Distributed Process ◽  
Generate Process ◽  
And Control

The objective of this research is to develop a methodology of distributed process planning and its execution control for job shop operations. The manufacturing processes of job shop operations are rather complex, especially at shop floors where highly mixed products in small batch sizes are handled simultaneously. In addition to the fluctuating job shop operations, unpredictable events like job delay, urgent job insertion, fixture shortage, missing tool, and even machine break-down, are regularly challenging the job shop operations. Targeting the fluctuations, this research proposes a DPP (distributed process planning) approach to generate process plans that are responsive and adaptive to the changes. In this paper, a function block enabled approach is introduced. It is expected that the new approach can largely enhance the dynamism of fluctuating job shop operations.

Function Block-Based Integration Mechanisms for Adaptive and Flexible Cloud Manufacturing

2015 ◽  
Author(s):  
Xi Vincent Wang ◽  
Lihui Wang
Keyword(s):  
Data Storage ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Function Block ◽  
Flexible Architecture ◽  
Function Blocks ◽  
Integration Mechanisms ◽  
Manufacturing Facilities ◽  
Block Based ◽  
And Function

Cloud Computing is the new enabling technology that offers centralised computing, flexible data storage, and scalable services. In the manufacturing context, it is possible to extend the Cloud technology for integrating and provisioning manufacturing facilities and capabilities in terms of Cloud services. In this paper, a function block-based integration mechanism is developed to integrate various types of manufacturing facilities. A Cloud-based architecture is also deployed to provide a service pool which maintains these facilities in terms of manufacturing services. The proposed framework and mechanisms are evaluated by implementations. In practice, it is possible to establish an integrated manufacturing environment across multiple levels with the support of manufacturing Cloud and function blocks. It provides a flexible architecture as well as adaptive and integration methodologies for the Cloud manufacturing system.

Overview of an Adaptive Setup Planning Approach for Job Shop Operations

2009 ◽  
Author(s):  
Lihui Wang
Keyword(s):  
Decision Making ◽  
Job Shop ◽  
Planning System ◽  
Shop Floor ◽  
Setup Planning ◽  
Planning Stage ◽  
Planning Approach ◽  
Job Shop Operations

This paper presents an overview of an adaptive setup planning system that considers both the availability and capability of machines on a shop floor. It integrates scheduling functions at setup planning stage, and utilizes a two-step decision-making strategy for generating machine-neutral and machine-specific optimal setup plans. The objective is to enable adaptive setup planning for dynamic machining job shop operations. Particularly, this paper documents basic algorithms and architecture of the setup planning system for dynamically assigned machines. It is then validated through a case study.

Virtual Function Block Mechanism in the Cloud Manufacturing Environment

2013 ◽  
Vol 694-697 ◽  
pp. 2438-2441 ◽  
Author(s):  
Xi Vincent Wang ◽  
Xun W Xu
Keyword(s):  
Service Oriented Architecture ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Manufacturing Environment ◽  
Function Block ◽  
Integration Mechanism ◽  
Data Flows ◽  
Service Oriented ◽  
Function Blocks ◽  
Block Based

CManufacturing is a new manufacturing model that has evolved from Service-Oriented Architecture, networked manufacturing and CComputing. It provides intelligent, interoperable and distributed manufacturing model for the industry. This paper introduces a resource integration mechanism in the Cloud Manufacturing environment. Function Block technology is discussed from the Cloud Manufacturing perspective in detail. Next, a novel integration mechanism is proposed, namely the Virtual Function Block. Based on physical Function Blocks and software agents, Virtual Function Blocks are able to manipulate and integrate manufacturing resources via event states and data flows. During implementation, Creo Parametric was integrated as a Cloud Service with the help of VFBs to evaluate the mechanism.

scholarly journals Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4836
Author(s):  
Liping Zhang ◽  
Yifan Hu ◽  
Qiuhua Tang ◽  
Jie Li ◽  
Zhixiong Li
Keyword(s):  
Decision Making ◽  
Data Base ◽  
Real Time ◽  
Manufacturing Industry ◽  
Job Shop ◽  
Data Driven ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Production Data ◽  
Online Decision Making

In modern manufacturing industry, the methods supporting real-time decision-making are the urgent requirement to response the uncertainty and complexity in intelligent production process. In this paper, a novel closed-loop scheduling framework is proposed to achieve real-time decision making by calling the appropriate data-driven dispatching rules at each rescheduling point. This framework contains four parts: offline training, online decision-making, data base and rules base. In the offline training part, the potential and appropriate dispatching rules with managers’ expectations are explored successfully by an improved gene expression program (IGEP) from the historical production data, not just the available or predictable information of the shop floor. In the online decision-making part, the intelligent shop floor will implement the scheduling scheme which is scheduled by the appropriate dispatching rules from rules base and store the production data into the data base. This approach is evaluated in a scenario of the intelligent job shop with random jobs arrival. Numerical experiments demonstrate that the proposed method outperformed the existing well-known single and combination dispatching rules or the discovered dispatching rules via metaheuristic algorithm in term of makespan, total flow time and tardiness.

scholarly journals Leveraging Graphical User Interface Automation for Generic Robot Programming

Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Tudor B. Ionescu
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Programming Models ◽  
Shop Floor ◽  
Robot Programming ◽  
User Interactions ◽  
Programming Environments ◽  
Automated Generation ◽  
Novel Approach ◽  
Block Based

A novel approach to generic (or generalized) robot programming and a novel simplified, block-based programming environment, called “Assembly”, are introduced. The approach leverages the newest graphical user interface automation tools and techniques to generate programs in various proprietary robot programming environments by emulating user interactions in those environments. The “Assembly” tool is used to generate robot-independent intermediary program models, which are translated into robot-specific programs using a graphical user interface automation toolchain. The generalizability of the approach to list, tree, and block-based programming is assessed using three different robot programming environments, two of which are proprietary. The results of this evaluation suggest that the proposed approach is feasible for an entire range of programming models and thus enables the generation of programs in various proprietary robot programming environments. In educational settings, the automated generation of programs fosters learning different robot programming models by example. For experts, the proposed approach provides a means for generating program (or task) templates, which can be adjusted to the needs of the application at hand on the shop floor.

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