Visualize movement lines with location data! Practical methods for movement-line analysis to reduce on-site waste

On-site locations (such as factories and construction sites) see many workers and vehicles moving around the premises every day. Hidden in those movements may be "wasteful motions" that do not directly contribute to production. With labor shortages and the push for work-style reforms, reducing such waste and enabling limited personnel to work efficiently is an important challenge in site management.

One solution attracting attention is movement-line analysis that visualizes the movements of people and objects using location data. If you can capture by data "where," "how much," and "for how long" workers and forklifts move, you can objectively uncover on-site inefficiencies that were previously based on intuition. This article explains movement-line analysis in detail, from the basics to concrete procedures, and introduces practical methods to reduce on-site waste.

Contents

• What is movement-line analysis?

• On-site waste and the importance of optimizing movement lines

• Advantages of movement-line analysis using location data

• Methods for obtaining the location data needed for movement-line analysis

• Visualization and analysis methods for movement-line data

• Steps and key points for improving movement lines

• Obtain precise movement-line data with simple surveying using LRTK

• Frequently Asked Questions (FAQ)

What is movement-line analysis?

A "movement line" refers to the routes along which people or objects move. Examples include the routes workers walk from a material storage area to a work area inside a factory, or the trajectories forklifts follow inside a warehouse. Movement-line analysis is the method of recording and visualizing these movement routes and analyzing their patterns and issues.

Movement-line analysis is used in various fields. In retail, customer in-store routes are analyzed to help improve store layout; in offices, employee movement in work areas is captured to inform office reconfiguration. Movement-line analysis is particularly notable in "on-site" production and work environments—such as factories, logistics warehouses, and construction sites—for improving work efficiency and safety.

The goal of movement-line analysis is to reduce wasted movement and improve work efficiency. By visualizing the movements of people and vehicles with data, previously overlooked inefficiencies (like detours and duplicated movements) can be discovered. Optimizing movement lines can lead to shorter work times, improved safety, and reduced burden on workers. In the next chapter, we’ll look at specific on-site "wastes" and how movement-line analysis can solve them.

On-site waste and the importance of optimizing movement lines

In manufacturing and construction sites, it is said that there are seven types of wasteful elements. One of them is the "waste of motion" (unnecessary movements or actions). For example, frequently going back and forth between the warehouse and the work area to fetch necessary tools, or having to take long detours because of poor layout—these are wastes of motion. Accumulated wasteful movement time can lead to decreased productivity and increased worker fatigue.

By using movement-line analysis, such wasteful movements at the site can be visualized. Specifically, the following issues can be solved based on data:

• Inefficient layouts: If work lines cross and become complicated, wasted passing and conflicts between workers or between people and vehicles occur. By analyzing movement-line data, you can consider optimal layout changes such as relocating material storage or equipment.

• Increased travel distance/time: If the total distance traveled in a day is too long or a particular process takes a lot of time for movement, it’s a red flag. Visualize where and which processes have the most waste, then place necessary items along frequently used routes or shorten movement lines to address the problem.

• Congestion and waiting: Movement-line analysis can also detect issues where workers cluster and cannot move, or where forklifts cause congestion. For crowded points, consider reviewing work procedures, changing staff allocation, or improving aisle width as safety measures.

• Human errors and safety risks: Complex movement lines can cause human errors or collisions. Identify intersections of people and vehicles and implement safety measures such as installing fences or making routes one-way to reduce risks.

Thus, data-backed improvements from movement-line analysis are crucial for reducing on-site waste and improving safety. Layout changes based solely on intuition or experience can miss problems, but presenting objective numbers makes it easier to gain internal buy-in and implement improvements smoothly.

Advantages of movement-line analysis using location data

Traditionally, to identify wasteful movements on-site, managers observed workers directly at the site or recorded long hours of footage with video cameras for later review. However, these methods place a heavy burden on people and are subjective, making it difficult to accurately capture all inefficiencies.

This is where location data obtained from GPS and sensors becomes useful. If workers or vehicles carry location-tracking devices, their routes and dwell times can be recorded automatically. Movement-line analysis using digital location data offers the following advantages:

• Visualization with objective data: All movement histories can be recorded as data without relying on human memory or intuition. Facts like "who went back and forth how many times" and "which routes consumed time" are shown numerically, increasing the persuasiveness of identified issues.

• Long-term and wide-area analysis: Tracking movements over weeks or months, not just a single day, reveals daily and weekly trends. Patterns such as certain lines becoming congested during busy periods can be detected from the data. In large sites, sensor networks can capture movements in areas that are hard for people to monitor directly.

• Efficient data collection: Once the system is implemented, data accumulates automatically. Managers don’t need to continuously watch, and data collection runs in parallel with other tasks. With real-time systems, anomalies can be detected and addressed immediately.

• Quantitative evaluation of improvement effects: After implementing improvements, their effects can be evaluated with data. For example, you can quantify how much total travel distance was reduced or whether dwell times decreased after changing movement lines. This allows objective verification of measures and informs further improvements.

Movement-line analysis using location data thus becomes a powerful tool for on-site improvement. The next chapter covers methods to obtain the data needed for actual movement-line analysis.

Methods for obtaining the location data needed for movement-line analysis

To perform movement-line analysis, you first need a system to measure and record the positions of people and vehicles. Available technologies and devices differ depending on whether the environment is indoors or outdoors. Below are common methods to obtain location data.

• GPS (GNSS): Uses satellite positioning systems to measure location. It is suitable for outdoor use; handheld GNSS devices carried by workers or vehicle-mounted GPS equipment can record movement routes. Standard GPS accuracy is on the order of several meters, but by using a correction technique called RTK (Real-Time Kinematic) mentioned later, centimeter-level high-precision positioning (cm level accuracy (half-inch accuracy)) is also possible.

• Bluetooth beacons: Widely used indoors. Small transmitters (beacons) installed on ceilings or walls periodically emit signals that are received by receivers carried by people or carts to estimate position. Depending on the number and spacing of beacons, indoor positions can be determined with meter-level accuracy. They are relatively inexpensive and easy to add later.

• UWB (Ultra-Wideband): A technology that enables high-precision indoor positioning. Using dedicated tags and receiving antennas, real-time positioning with accuracy of several tens of centimeters or less is possible. It is increasingly used for high-precision tracking of people and equipment in factories and hospitals, though equipment costs are somewhat higher.

• RFID/barcodes: Attach IC tags or barcodes to people or items and track movement history by reading them when passing gates. This is not continuous real-time positioning but is useful in logistics warehouses to manage item movement or to record when workers pass fixed checkpoints.

• Wi-Fi positioning: Estimates rough location using existing Wi-Fi access points. No dedicated devices are required, but accuracy is coarse (on the order of several meters), so it’s more suitable for coarse location awareness than detailed movement-line analysis.

• Camera image analysis: Analyzes footage from ceiling-mounted surveillance cameras to track people or forklifts. While there are privacy and blind-spot issues, a strength is that fine-grained movements and behaviors can be analyzed from video. Advances in AI image analysis are making automatic detection of complex movements increasingly possible.

Many technologies can acquire location information, each differing in accuracy, cost, and installation effort. Choose the method appropriate to the site’s scale and purpose. For example, a GPS device may be sufficient to capture the rough movements of forklifts around a facility, whereas UWB or many beacons are better if you want to analyze each worker’s detailed movements inside a factory. Hybrid solutions that combine these—for example, GPS outdoors and BLE beacons indoors—are increasingly available for seamless tracking.

Visualization and analysis methods for movement-line data

Once location data is obtained, the next step is to visualize and analyze it. Massive coordinate data can be made intuitively understandable through appropriate visualization, revealing how the site actually operates. Here are the main visualization and analysis methods.

• Trajectory maps (spaghetti diagrams): Overlay movement routes of people or vehicles as lines on a map or site layout. When multiple workers’ trajectories intertwine, it’s often called a "spaghetti diagram." From this, you can see at a glance which routes are frequently used and whether there are unnecessary detours.

• Heatmaps: Show dwell time or passage counts at locations using color intensity. Areas shown in deep red indicate places where many people stay for long periods or that are frequently passed. Heatmaps highlight site bottlenecks (places prone to congestion), popular aisles, and underused spaces.

• Distance/time graphs: Use bar charts or line graphs to show total travel distance or time spent moving for each worker or vehicle over a given period. This enables quantitative comparisons such as who walks the most or which team bears the greatest movement burden. Extremely large values warrant investigation, and comparing graphs before and after improvements can serve as evidence of effect.

• Dwell-time analysis: Calculates how long stops occur at each point. For example, how many minutes were spent searching for tools at the material storage, or how long waiting for inspection took. Locations with long dwell times indicate potential for improving work processes or staff allocation.

• Real-time monitoring: More of a management application than analysis, systems can display who is where and which route a forklift is currently traveling in real time. This enables safety applications such as issuing alerts when someone enters a hazardous area.

After visualization and analysis reveal hints for improvement, implement concrete improvement actions. For example, if movement-line data shows that material storage is far from Process A and movement time is long, propose relocating the material storage closer. If data shows frequent passing congestion in Area B, consider widening aisles or making routes one-way.

Importantly, evaluate the effects of such improvements with data afterward. Compare movement-line data before and after to confirm whether travel distances shortened or dwell times decreased. If effects are insufficient, try alternative measures and continue the PDCA cycle to pursue continuous optimization. A data-driven approach reduces waste more reliably than traditional intuition-based methods.

Steps and key points for improving movement lines

So how should on-site improvements via movement-line analysis actually proceed? Below is a step-by-step outline of the basic process.

• Form a hypothesis about the issue: First, hypothesize where waste exists on site. Conduct interviews with workers or observe the site to identify issues such as "Is there too much movement for ○○?" or "Is waiting occurring at △△?" Having hypotheses helps focus data collection and analysis efficiently.

• Obtain location data: Collect the data needed to test the hypotheses. Refer to the aforementioned technologies and record location information using the method suitable for the site. For example, attach GPS loggers to outdoor heavy equipment or distribute UWB tags to track indoor workers in detail. The important point is to collect data that can quantify current waste.

• Visualize and analyze data: Create graphs and maps from the collected location data to test hypotheses. Confirm whether your hypotheses are supported by data—for example, "As expected, Process ○○ had a lot of unnecessary movement," or "△△ took more time than expected." If necessary, collect additional data and dig deeper into causes.

• Implement improvement measures: Based on the analysis, implement concrete measures such as layout changes, establishing rules, or revising staff allocation. Small changes are fine. Change movement lines on site and observe the effects.

• Evaluate effects and plan next measures: Compare data before and after improvements to measure effects, such as a ○% reduction in movement time or fewer dwell occurrences. If improvements are effective, standardize them and move on to other issues. If effects are insufficient, reconsider causes and try different measures. Continuously running the PDCA cycle will steadily improve on-site productivity.

Improving on-site movement lines is not completed overnight. However, by proceeding with improvements backed by objective data, waste can be steadily reduced. It’s important to incorporate feedback from site staff and optimize step by step within feasible limits.

Obtain precise movement-line data with simple surveying using LRTK

To perform more advanced movement-line analysis, accurately capturing detailed location information on site is key. However, traditional surveying required expertise and expensive equipment, making it difficult for site staff to perform on their own.

Enter simple surveying with LRTK. LRTK is a pocket-sized surveying device that attaches to a smartphone and enables centimeter-level position measurement easily even for non-experts. By attaching a lightweight device of about 165 g to a smartphone and using a dedicated app, you can instantly record latitude, longitude, and elevation for arbitrary points on site.

Using LRTK makes it easy to create high-precision site maps and link accurate coordinate information to movement-line data. For example, if you measure and register the position of a newly installed machine with LRTK, you can precisely analyze which equipment areas cause frequent stops in workers’ movement data. Also, by measuring positions of equipment and aisles with LRTK after layout changes, comparisons of movement lines before and after become more accurate.

Tasks that previously required a surveying specialist can now be completed quickly by site staff using LRTK. This is a major advantage for promoting on-site DX (digital transformation). Why not lower the barrier to datafying on-site "movement" by leveraging LRTK, a simple surveying tool anyone can use? For more detailed information, see the LRTK official site: https://www.lrtk.lefixea.com

Frequently Asked Questions (FAQ)

Q1. On what kinds of sites is movement-line analysis effective? A. Movement-line analysis is effective at any on-site location where people and vehicles move, large or small—such as manufacturing factories, distribution centers, and construction sites. For example, analyzing worker and parts movement in factories, picking movements in warehouses, or movements of heavy machinery and workers on construction sites can lead to efficiency gains. It is also useful in hospitals, commercial facilities, and other places to visualize human movement for service improvement.

Q2. Do I need a large investment to start movement-line analysis? A. Not necessarily. For small sites, you can start with analog methods like manually recording movement lines on a floor plan. Even for digital approaches, it’s recommended to begin by trialing relatively inexpensive GPS loggers or commercial beacons to collect data. When scaling up, expand in stages and start with the minimum necessary equipment to verify effects while keeping costs down.

Q3. Are there privacy or surveillance concerns when tracking location data? A. Some workers may feel uneasy about being tracked. When introducing such systems, it’s important to clearly communicate that the purpose is operational efficiency and safety management—not personal surveillance. Managing data by ID instead of personal names, restricting use of collected data solely to improvement activities, and establishing rules are effective privacy measures. Share with staff that the analysis aims to improve working conditions.

Q4. What level of positioning accuracy is needed for movement-line analysis? A. Required accuracy depends on the application. For example, if you want to capture the rough movements of heavy machinery on a large construction site, GPS with meter-level error may suffice. Conversely, if you want to analyze fine-grained movements of workers inside a factory to inform workstation layouts, 1 m error is insufficient and centimeter-level accuracy—such as UWB or LRTK—is desirable. Select the technology based on the accuracy needed for your analysis.

Q5. How does LRTK help with movement-line analysis? A. LRTK allows easy acquisition of high-precision location data. Using LRTK in movement-line analysis lets you measure exact coordinates of reference points and equipment to create maps, and record outdoor movements of people and vehicles at centimeter-level accuracy. Because LRTK can capture subtle positional shifts that were previously unmeasurable, it’s useful for evaluating the effects of small layout changes and designing detailed movement lines. Since it enables in-house surveying without specialists, movement-line analysis can be implemented at lower cost and in a shorter time.