An Implementation of Web-based Machining Operation Planning

AbstractThis paper introduces a machining operation planning system for practical use in small and medium sized manufacturers. The system passes through two stages: manual input of required information and semi-automated generation of an operation plan. At the first stage, removal volumes out of a workpiece and their reference details on the part drawing are translated into the specific machining features manually. The operations to be performed for each feature are then selected from the operation list related to the feature. At the second stage, the cutting tool for each operation is determined with its proper cutting conditions by using a rule-based algorithm and retrieving a machining database gradually updated. The web interface makes it possible for the manufacturers to keep a record of their machining practice in the database and obtain the favorable data from the various sources when needed. An example is shown to demonstrate the usefulness of the system

Resilience in the Surgical Scheduling to Support Adaptive Scheduling System

Operating Room (OR) managers frequently encounter uncertainties related to real-time scheduling, especially on the day of surgery. It is necessary to enable earlier identification of uncertainties occurring in the perioperative environment. This study aims to propose a framework for resilient surgical scheduling by identifying uncertainty factors affecting the real-time surgical scheduling through a mixed-methods study. We collected the pre- and post-surgical scheduling data for twenty days and a one-day observation data in a top-tier general university hospital in South Korea. Data were compared and analyzed for any changes related to the dimensions of uncertainty. The observations in situ of surgical scheduling were performed to confirm our findings from the quantitative data. Analysis was divided into two phases of fundamental uncertainties categorization (conceptual, technical and personal) and uncertainties leveling for effective decision-making strategies. Pre- and post-surgical scheduling data analysis showed that unconfirmed patient medical conditions and emergency cases are the main causes of frequent same-day surgery schedule changes, with derived factors that affect the scheduling pattern (time of surgery, overtime surgery, surgical procedure changes and surgery duration). The observation revealed how the OR manager controlled the unexpected events to prevent overtime surgeries. In conclusion, integrating resilience approach to identifying uncertainties and managing event changes can minimize potential risks that may compromise the surgical personnel and patients’ safety, thereby promoting higher resilience in the current system. Furthermore, this strategy may improve coordination among personnel and increase surgical scheduling efficiency