Continuous ergonomic risk perception for manual assembly operations using wearable multi-sensor posture estimation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wei Fang ◽  
Mingyu Fu ◽  
Lianyu Zheng
Keyword(s):  
Real Time ◽  
Assessment Method ◽  
Shop Floor ◽  
Activity Data ◽  
Manual Assembly ◽  
Wearable System ◽  
Content Type ◽  
System A ◽  
Posture Estimation ◽  
Assembly Operations

Purpose This paper aims to perform the real-time and accurate ergonomics analysis for the operator in the manual assembly, with the purpose of identifying potential ergonomic injuries when encountering labor-excessive and unreasonable assembly operations. Design/methodology/approach Instead of acquiring body data for ergonomic evaluation by arranging many observers around, this paper proposes a multi-sensor based wearable system to track worker’s posture for a continuous ergonomic assessment. Moreover, given the accurate neck postural data from the shop floor by the proposed wearable system, a continuous rapid upper limb assessment method with robustness to occasional posture changes, is proposed to evaluate the neck and upper back risk during the manual assembly operations. Findings The proposed method can retrieve human activity data during manual assembly operations, and experimental results illustrate that the proposed work is flexible and accurate for continuous ergonomic assessments in manual assembly operations. Originality/value Based on the proposed multi-sensor based wearable system for posture acquisition, a real-time and high-precision ergonomics analysis is achieved with the postural data arrived continuously, it can provide a more objective indicator to assess the ergonomics during manual assembly.

Development of an integrated real time dispatching system

2014 ◽  
Vol 25 (7) ◽  
pp. 980-997 ◽  
Author(s):  
Yanting Ni ◽  
Yuchen Li ◽  
Jin Yao ◽  
Jingmin Li
Keyword(s):  
Real Time ◽  
Information Integration ◽  
Production Scheduling ◽  
Performance Metrics ◽  
Dynamic Scheduling ◽  
Shop Floor ◽  
Content Type ◽  
The Real ◽  
Work In Process ◽  
Dispatching Algorithm

Purpose – In a complex semiconductor manufacturing system (SMS) environment, the implementation of dynamic production scheduling and dispatching strategies is critical for SMS distributed collaborative manufacturing events to make quick and correct decisions. The purpose of this paper is to assist manufacturers in achieving the real time dispatching and obtaining integrated optimization for shop floor production scheduling. Design/methodology/approach – In this paper, an integrated model is designed under assemble to order environment and a framework of a real time dispatching (IRTD) system for production scheduling control is presented accordingly. Both of the scheduling and ordering performances are integrated into the days of inventory based dispatching algorithm, which can deal with the multiple indicators of dynamic scheduling and ordering in this system to generate the “optimal” dispatching policies. Subsequently, the platform of IRTD system is realized with four modules function embedded. Findings – The proposed IRTD system is designed to compare the previous constant work in process method in the experiment, which shows the better performance achievement of the IRTD system for shop floor production dynamic scheduling and order control. The presented framework and algorithm can facilitate real time dispatching information integration to obtain performance metrics in terms of reliability, availability, and maintainability. Research limitations/implications – The presented system can be further developed to generic factory manufacturing with the presented logic and architecture proliferation. Originality/value – The IRTD system can integrate the real time customer demand and work in process information, based on which manufacturers can make correct and timely decisions in solving dispatching strategies and ordering selection within an integrated information system.

scholarly journals Real Time Implementation of Learning-Forgetting Models for Cycle Time Predictions of Manual Assembly Tasks after a Break

2020 ◽  
Vol 12 (14) ◽  
pp. 5543
Author(s):  
Steven Hoedt ◽  
Arno Claeys ◽  
El-Houssaine Aghezzaf ◽  
Johannes Cottyn
Keyword(s):  
Real Time ◽  
Cycle Time ◽  
Mixed Model ◽  
Manufacturing Companies ◽  
Manual Assembly ◽  
Time Prediction ◽  
Curve Model ◽  
Assembly Operations ◽  
Assembly Tasks ◽  
Mixed Model Assembly

Industry 4.0 provides a tremendous potential of data from the work floor. For manufacturing companies, these data can be very useful in order to support assembly operators. In literature, a lot of contributions can be found that present models to describe both the learning and forgetting effect of manual assembly operations. In this study, different existing models were compared in order to predict the cycle time after a break. As these models are not created for a real time prediction purpose, some adaptations are presented in order to improve the robustness and efficiency of the models. Results show that the MLFCM (modified learn-forget curve model) and the PID (power integration diffusion) model have the greatest potential. Further research will be performed to test both models and implement contextual factors. In addition, since these models only consider one fixed repetitive task, they don’t target mixed-model assembly operations. The learning and forgetting effect that executing each assembly task has on the other task executions differs based on the job similarity between tasks. Further research opportunities to implement this job similarity are listed.

Textbook ranking and an assessment method and system: a case study using surveying textbooks

2020 ◽  
Vol 38 (5/6) ◽  
pp. 861-880
Author(s):  
Chien-Min Kuo ◽  
Kuan-Yu Chen ◽  
Yi-Ching Lin
Keyword(s):  
Assessment Method ◽  
Added Value ◽  
Value Analysis ◽  
Content Type ◽  
Domain Experts ◽  
Work Related ◽  
System A ◽  
Computer Aided

Purpose Teachers, students, librarians, scholars and domain experts often spend a lot of time and effort to select good and suitable textbooks. This study aims to propose and construct a computer-aided bibliometric system to rate textbooks. Through the software system designed here, the quality of every textbook can be easily and quickly known. This system will benefit both scholars and librarians. Design/methodology/approach Four methods were used to evaluate textbooks in this study, including: questionnaire recommendation analysis, dissertation citation analysis, library circulation analysis and bibliography analysis. The system architecture includes three subsystems: the textbook indexing and searching subsystem, the statistics added-value analysis subsystem and the citation report inquiry subsystem. An example demonstrates the usability and validity of the proposed method and system. The example uses surveying textbooks. The following percentages were used in the correlation calculation: textbook citation percentage (TCP), textbook library circulation percentage (TLP) and textbook recommend percentage (TRP). Findings There are three textbook assessment methods applied in this study, including: dissertation citation, library circulation and questionnaire recommendation. Dissertation citations for textbooks have a high correlation value with library circulation. The frequency correlation calculation was 0.7, while the TCP, TLP and TRP correlation calculation was 0.84. Therefore, the dissertation citation method can be accepted to evaluate textbooks effectively. Originality/value To the best of the authors’ knowledge, this is the first work related to evaluating surveying textbooks using a computer-aided bibliometrics system that can deal with large amounts of data and generate results quickly. This can be applied to other fields as well.

scholarly journals Utilising low cost RGB-D cameras to track the real time progress of a manual assembly sequence

2019 ◽  
Vol 40 (6) ◽  
pp. 925-939 ◽  
Author(s):  
John Oyekan ◽  
Axel Fischer ◽  
Windo Hutabarat ◽  
Christopher Turner ◽  
Ashutosh Tiwari
Keyword(s):  
Computer Vision ◽  
Big Data ◽  
Machine Vision ◽  
Real Time ◽  
Production Line ◽  
Industry 4.0 ◽  
Time Machine ◽  
Manual Assembly ◽  
Content Type ◽  
Assembly Task

Purpose The purpose of this paper is to explore the role that computer vision can play within new industrial paradigms such as Industry 4.0 and in particular to support production line improvements to achieve flexible manufacturing. As Industry 4.0 requires “big data”, it is accepted that computer vision could be one of the tools for its capture and efficient analysis. RGB-D data gathered from real-time machine vision systems such as Kinect ® can be processed using computer vision techniques. Design/methodology/approach This research exploits RGB-D cameras such as Kinect® to investigate the feasibility of using computer vision techniques to track the progress of a manual assembly task on a production line. Several techniques to track the progress of a manual assembly task are presented. The use of CAD model files to track the manufacturing tasks is also outlined. Findings This research has found that RGB-D cameras can be suitable for object recognition within an industrial environment if a number of constraints are considered or different devices/techniques combined. Furthermore, through the use of a HMM inspired state-based workflow, the algorithm presented in this paper is computationally tractable. Originality/value Processing of data from robust and cheap real-time machine vision systems could bring increased understanding of production line features. In addition, new techniques that enable the progress tracking of manual assembly sequences may be defined through the further analysis of such visual data. The approaches explored within this paper make a contribution to the utilisation of visual information “big data” sets for more efficient and automated production.

A double decoupling postponement approach for integrated mixed flow production systems

Kybernetes ◽  
2015 ◽  
Vol 44 (5) ◽  
pp. 705-720 ◽  
Author(s):  
Yanting Ni ◽  
Yi Wang
Keyword(s):  
Real Time ◽  
Production Planning ◽  
Production Systems ◽  
Shop Floor ◽  
Mixed Flow ◽  
Planning And Scheduling ◽  
Content Type ◽  
Production Planning And Scheduling ◽  
Work In Process

Purpose – In a mixed flow production environment, interactions between production planning and scheduling are critical for mixed flow distributed manufacturing management. The purpose of this paper is to assist manufacturers in achieving real-time ordering and obtaining integrated optimization of shop floor production planning and scheduling for mixed flow production systems. Design/methodology/approach – A double decoupling postponement (DDP) approach is presented for production dispatch control, and an integrated model is designed under an assemble to order (ATO) environment. To generate “optimal” lots to fulfil real-time customer requests, constant work in progress (CONWIP) and days of inventory dispatching algorithms are embedded into the proposed DDP model, which can deal with real-time ordering and dynamic scheduling simultaneously. Subsequently, a case study is conducted, and experiments are carried out to verify the presented method. Findings – The proposed DDP model is designed to upgrade a previous CONWIP method in the case study company, and the proposed model demonstrates better performance for the integration of production planning and scheduling in mixed flow manufacturing. As a result, the presented operation mechanism can reflect real-time ordering information to shop floor scheduling and obtain performance metrics in terms of reliability, availability and maintainability. Research limitations/implications – The presented model can be further proliferated to generic factory manufacturing with the proposed logic and architecture. Originality/value – The DDP model can integrate real-time customer orders and work in process information, upon which manufacturers can make correct decisions for dispatch strategies and order selection within an integrated system.

A Highly Efficient and Optimised Simulation Based Multi objective Decision-Making for FMS Control

2018 ◽  
Vol 6 (6) ◽  
pp. 98
Author(s):  
Shreyanshu Parhi ◽  
S. C. Srivastava
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Manufacturing Industry ◽  
Simulation Software ◽  
Shop Floor ◽  
Simulation Tool ◽  
Routing Flexibility ◽  
Decision System ◽  
Multi Objective ◽  
Arena Simulation

Optimized and efficient decision-making systems is the burning topic of research in modern manufacturing industry. The aforesaid statement is validated by the fact that the limitations of traditional decision-making system compresses the length and breadth of multi-objective decision-system application in FMS.  The bright area of FMS with more complexity in control and reduced simpler configuration plays a vital role in decision-making domain. The decision-making process consists of various activities such as collection of data from shop floor; appealing the decision-making activity; evaluation of alternatives and finally execution of best decisions. While studying and identifying a suitable decision-making approach the key critical factors such as decision automation levels, routing flexibility levels and control strategies are also considered. This paper investigates the cordial relation between the system ideality and process response time with various prospective of decision-making approaches responsible for shop-floor control of FMS. These cases are implemented to a real-time FMS problem and it is solved using ARENA simulation tool. ARENA is a simulation software that is used to calculate the industrial problems by creating a virtual shop floor environment. This proposed topology is being validated in real time solution of FMS problems with and without implementation of decision system in ARENA simulation tool. The real-time FMS problem is considered under the case of full routing flexibility. Finally, the comparative analysis of the results is done graphically and conclusion is drawn.

Neurochemistry of L-Glutamate Transport in the CNS: A Review of Thirty Years of Progress

2001 ◽  
Vol 66 (9) ◽  
pp. 1315-1340 ◽  
Author(s):  
Vladimir J. Balcar ◽  
Akiko Takamoto ◽  
Yukio Yoneda
Keyword(s):  
Molecular Biology ◽  
Glutamate Transport ◽  
Mammalian Brain ◽  
Activity Data ◽  
System A ◽  
Recent Developments ◽  
The Central Nervous System ◽  
Health And Disease ◽  
Disease Analysis

The review highlights the landmark studies leading from the discovery and initial characterization of the Na+-dependent "high affinity" uptake in the mammalian brain to the cloning of individual transporters and the subsequent expansion of the field into the realm of molecular biology. When the data and hypotheses from 1970's are confronted with the recent developments in the field, we can conclude that the suggestions made nearly thirty years ago were essentially correct: the uptake, mediated by an active transport into neurons and glial cells, serves to control the extracellular concentrations of L-glutamate and prevents the neurotoxicity. The modern techniques of molecular biology may have provided additional data on the nature and location of the transporters but the classical neurochemical approach, using structural analogues of glutamate designed as specific inhibitors or substrates for glutamate transport, has been crucial for the investigations of particular roles that glutamate transport might play in health and disease. Analysis of recent structure/activity data presented in this review has yielded a novel insight into the pharmacological characteristics of L-glutamate transport, suggesting existence of additional heterogeneity in the system, beyond that so far discovered by molecular genetics. More compounds that specifically interact with individual glutamate transporters are urgently needed for more detailed investigations of neurochemical characteristics of glutamatergic transport and its integration into the glutamatergic synapses in the central nervous system. A review with 162 references.

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.

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