In this regard, the prerequisite is continuous monitoring of the production process to obtain direct data at the workplace. However, this may shoulder additional responsibilities of the current workload, which may negatively affect work performance. Recently, industrial Internet of Things technology with advanced sensors and long-range telecommunication equipment have enabled us to receive high-quality data in the workplace.
Therefore, the objective of this study is to develop a production process monitoring system that provides two main functions: (i) production progress monitoring and (ii) production resource positioning. Next, let's discuss how to select the appropriate process data and determine the data capture method. Production progress is measured by comparing the obtained field data with the planned production plan.
The developed manufacturing process monitoring system is illustrated and demonstrated with the case study of ship block assembly monitoring.
Introduction
- Background
- Motivation
- Objective
- Outline of the thesis
The location where the data is obtained is the same as the location of the product. In other words, the position of the product indicates the current process and this can also be converted into progress information. A building, which represents the product in this case, does not move from the beginning to the end of the construction.
Due to the size of the product, many features are comparable to the construction kit. In this regard, the manager must monitor not only the progress of production, but also the spatial condition of the products.
Literature Survey
Progress monitoring
- Shop-floor
- Building industry
- Shipbuilding industry
To solve the causes that lie in unrealistic planning and unforeseen site conditions, automated activity tracking subsystem based on image recognition, automatic material tracking subsystem and a mobile computer-aided communication environment are developed (Rebolj et al. 2008). The results of progress comparison between as-planned and as-built executions are visualized in the D4AR (4D Augmented Reality) environment using a traffic light metaphor (Golparvar-Fard et al. 2009). Among these process planning activities, the assembly process planning is by far the most important as it determines what happens in the other planning activities and it also takes more time to plan than all the others (Cho et al. 1996).
To monitor this harsh environment, a sensor-based remote monitoring technique for ship block assembly has been studied. Remote monitoring of assembly status makes it possible to minimize marginal errors during the ship block assembly process and helps in efficient ship construction (Lee 2009). The RFID tag is attached to the raw material of the block, metal plate in this case.
During the sheet forming process, the absence of the material affects the schedule in a negative way. To find out the absence of the plate and analysis, a prototype of the system was implemented with hardware and application software (Noh and Shin 2009). This current data from welding is used to develop a method to identify the work progress of blocks through a correlation equation between the weld length and arc time of the block (Ahn et al. 2011).
The assembly of ship blocks has similar characteristics to the construction industry, so it should be called construction and not assembly. The images acquired by the camera are then processed to extract the blocky areas. The estimated information is provided to the operator to effectively manage the block assembly schedule (Kim et al. 2015).
Wireless indoor positioning algorithm
- Triangulation
The idea of TDOA is to determine the relative position of the mobile transmitter by examining the difference in time of signal arrival across multiple metrics, rather than the absolute arrival time of TOA. Unlike TOA, time synchronization between the target and receiver is not necessary, but each receiver must be synchronized. As with the circle from TOA, TDOA can give the hyperboloid possibility of the target position.
When the distance between the receivers and the target is quite long, the direction can be calculated geometrically. To map the position on the 2-dimensional space, calculate the point of contact between the target plane and the direction vector. In the investigated studies, a method that uses both TODA and the Doppler model is to map the target that is far from the receiver (Basiri et al. 2012).
In indoor environments, it is difficult to find a Line-of-Sight (LOS) channel between the transmitter and the receiver. Another approach is to use the attenuation of the transmitted signal strength to estimate the distance of the mobile device in some set of measurement units. A method based on signal attenuation attempts to calculate the signal path loss due to propagation (Liu et al. 2007).
The accuracy of this method can be improved by using premeasured RSS contours centered at the receiver or multiple measurements at several base stations (Zhou et al. 2005). The central observation that suggests that positioning using AOA is possible is the following: if we know the positions for the vertices of a triangle and the angles at which an interior point "sees" the vertices, we can determine the position of the interior point. A method has been developed for all nodes to determine their orientation and position in an ad-hoc network where only a fraction of nodes have positioning capability, under the assumption that every node has AOA capability (Niculescu and Nath 2003).
The Production Progress Monitoring Method
- Problem statement
- Characteristics of the target manufacturing system
- Product, Process and Resource mapping
- Planning for the data acquisition
- Selection of the information to be acquired
- Planning for the data acquisition
- Production progress measurement
- Scoring method for the single part identification
- Grouping method for the product identification
- Production progress measurement
- The ship block assembly monitoring system
- Test environment
- Virtual BoM and operation schedule
- Simulation with monitoring program
In this chapter, the production progress monitoring method will be described with the case study of the curved panel block assembly monitoring system in the shipbuilding industry. The catalog of data that can be selected for the production process becomes more diverse as the characteristics of the manufacture are analyzed. Therefore, these two processes must be monitored first to measure the production progress. a) Main process of the curved block assembly.
From the job site to the small screw, there are no limits to resource definition. When assembling a curved block, it is necessary to select data that can be used to measure the progress of loading and welding. Several studies have been conducted in the shipbuilding industry to measure the progress of curved block production.
In research on curved block assembly, measuring the progress of block production using visual information was studied (Kim et al. 2015). All curved blocks in the field are mounted and assembled on pin inserts. By using weight measuring equipment on a pin jig, it is possible to achieve a change in the weight of the curved block.
All parts that are loaded into the curved block are transported by overhead crane. By grouping the parts loaded into the operation, the ID of each product is also measured. Additionally, loading operations are mostly processed in the early stage of the assembly process.
This system measures the production progress of the curved block using the weight data obtained from the overhead crane. Position of the trolley can be measured by obtaining the operation data of two linear actuators.
Manufacturing Resource Positioning Methods
Problem statement
The solution may be to build a mesh network or use long-range wireless communication technology, but these methods are difficult to manage and require significant costs. In this regard, we also studied and tested the method of data transmission using an acoustic signal.
Workspace estimation using the operation data of overhead cranes
- Absolute positioning of the overhead crane
- Relative positioning of a product
Given the linear movement of the trolley along the rail, linear distance measurement methods can be used to position the trolley. On the other hand, by installing an absolute positioning module on the cart, it is possible to position the cart without references. A bar code measurement sensor mounted on the trolley reads a bar code attached to the rail to detect the position of the trolley and thus intuitive coordination is possible.
To reduce the cost for installing the positioning module, a method using a visual marker can be applied. Visual marker is attached to the trolley and the camera records visual information of the workspace. Through the absolute position of the trolley, a loading position of the part is relatively measurable.
At this point, coordinate information for the main panel can be used to form the workspace of a curved block. However, the coordinate information for the parts is recognized as in Figure 4.6 below, part grouping and product workspace estimation is necessary. We developed part grouping and product workspace estimation method using load coordinates and weight of the parts.
Provided the thicknesses and densities of the main panels are the same, they have an area proportional to the weight. Through this sub-grouping and estimation method, loaded main panels are grouped and used to estimate the working area of the product. But only with the weight data, this method can be used when a shape of the product seen from above is square.
Acoustic signal positioning
- TDOA estimation
- Data transfer using sound source discretization
- Positioning and data transfer using microphone array
Virtual areas of the products are shown in red and a newly loaded component is shown in green. Despite these limitations, sound is one of the most important cues for locating noisy facilities. However, multiple facilities of the same type are operated in the same workplace, so it is difficult to identify the facility based on proper classification alone.
In this regard, we developed a method for positioning and data transfer with an acoustic signal cycle. However, an approximation of the correlation delay can be calculated in the frequency domain by computing the inverse Fourier transform of the cross spectrum. Using long wire to connect each microphone and DAQ has the risk of disconnection and signal distortion.
In other words, to estimate the direction of the sound source in 3 dimensional space, at least 4 microphones are needed. In the case of overhead crane moving in the 2-dimensional plane, the point of contact for the direction and the plane is mapping of the overhead crane. As described in the previous chapter, product identification is a prerequisite for the progress monitoring system.
Only with the direction of the sound source, it is limited to be used for measuring production progress. This signal is also used to determine the start and end of the data transfer phase as a protocol. Through this 2-phase acoustic signal method, both positioning and data transfer can be processed at the same time with one signal cycle.
Conclusion and Future research
Design and prototype implementation of the curved plate flow tracking and monitoring system using RFID. Paper presented at the 19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA Papers).
