For example, when applied to the transport of articles within factories, analyzing location and movement data makes it possible to optimize movement routes. Sometimes routes that appear on a map to be the shortest routes actually include areas that are difficult to traverse, so operators end up using unexpected routes instead. In some cases, workers use these alternative routes unconsciously, to avoid objects placed on designated movement routes, so they may not mention them in their reports. By identifying this phenomenon when it occurs, along with the cause of the phenomenon, and taking appropriate steps in response, worksites can not only optimize their movement routes but also achieve greater work efficiency and safety.
The Field Work Visualization Package also contributes to the monitoring and protection of workers. In some worksites, personnel may need to work at night, or on their own. If a wristband sensor detects that a worker is suffering from some sort of health issue, it notifies their supervisor and a response can be taken. Linking work environment and worker monitoring and communication functions provides workers with workplace environments in which they can enjoy peace of mind.
Furthermore, the solution can be used to provide alerts and analyze equipment abnormalities. Data is integrated with the systems used to manage equipment. This assists with sharing information in a timely fashion when an abnormality occurs and taking corrective action. The actions of personnel and equipment can also be compared using the same timeline when performing a follow-up analysis. This enables the visualization of the state of equipment and how it changed over time following the occurrence of the abnormality, along with the actions taken by personnel at the same time. This visualization contributes to the deliberation of improvement measures such as measures for optimizing personnel assignment and revising skill requirements.
The solution can also be used in the visualization of the movement of transport vehicles used in the field, such as forklifts, automatic guided vehicles (AGVs), and cranes. Movement bottleneck locations and routes can be quantitatively identified and the causes of these bottlenecks can be eliminated, which helps improve productivity significantly.
There are case examples of the solution being used to make actual productivity improvements. Information about operations, categorized as manual work, dolly movement, walking, and staying still, and location information used to determine if an operator is in their assigned work space, has been used to categorize work content as "primary work," "incidental work," and "other." Actual work times and standard work times for each operation have been graphed and compared. The data has been used to determine when the amount of incidental work had increased, and detailed data investigation found areas requiring improvement, such as major increases in dolly movement time in specific areas. The causes of these issues were analyzed, and countermeasures were put into effect. Pre- and post-improvement data were compared, and the outcomes of the improvements were analyzed. This analysis found that the improvements had increased the amount of time that could be spent on primary work and reduced the overall time required to perform work (Fig. 4).