Abstract
Logging and tracking raw materials, workpieces and engineered products for seamless and quick pulls is a complex task in the construction and shipbuilding industries due to lack of structured storage solutions. Additional uncertainty is introduced if workpieces are stacked and moved by multiple stakeholders without maintaining an active and up-to-date log of such movements. While there are frameworks proposed to improve workpiece pull times using a variety of tracking modes based on deterministic approaches, there is little discussion of cases wherein direct observations are sparse due to occlusions from stacking and interferences. Our work addresses this problem by: logging visible part locations and timestamps, through a network of custom designed observation devices; and building a graph-based model to identify events that highlight part interactions and estimate stack formation to search for parts that are not directly observable. By augmenting the site workers and equipment with our wearable devices, we avoid adding additional cognitive effort for the workers. Native building blocks of the graph-based model were evaluated through simulations. Experiments were also conducted in an active shipyard to validate our proposed system.
Highlights
Tracking and logging workpieces within a warehouse or storage yard is critical for industrial production and construction
It is not always possible to build inventory specific storage or maintain them through transition of inventory, due to a finite limit on storage space and need to maximize utilization of available space. This case is prevalent in shipbuilding and construction industries that deal with materials of diverse shapes and use open floor or unstructured environments for ad hoc storage [1,2]
The expected number of locations to search for in this case can be modeled as the expected number of guesses needed to find the correct location, given equal probability of finding the workpiece in each location
Summary
Tracking and logging workpieces within a warehouse or storage yard is critical for industrial production and construction. It is not always possible to build inventory specific storage or maintain them through transition of inventory, due to a finite limit on storage space and need to maximize utilization of available space This case is prevalent in shipbuilding and construction industries that deal with materials of diverse shapes and use open floor or unstructured environments for ad hoc storage [1,2]. Since workpieces getting stacked and moved around by a variety of stakeholders is the primary cause of occlusions and missing parts, our work attempts to identify and track the outcome of such events This allows us to propose a totem pole of search locations as locations of other workpieces with which they might be stacked along with. Limits and future work for our system are discussed in the Conclusions
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