Meta Smart Factory

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Case Studies – Food Industries
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Production & Labor Auto-Scheduling

Line Balancing


Kihívások

Scheduling problems in production become a mutual issue for many manufacturers today. Numerous issues based on inaccurate scheduling cause so many losses for producers.

Optimally assigning job orders to workstations and managing the employee dynamically and flexibly in real-time is becoming more difficult as production capacity is increasing and the production routing becomes more complex.

Assignment of operation to the resource is a key function to achieving operational efficiency and optimizing performance. All these apprehensions related to the production disappear with the correct production auto schedule.


Scenarios & Solutions

The solution that MSF provides managing the employee dynamically and flexibly in real-time using hidden capacity. In addition to this, assigning job orders to workstations optimally and planning instant production status changes.

The process is managed by MSF as follows; the operation data is transferred to the system and the artificial intelligence algorithm decides the number of people to be assigned to the relevant operation. While the algorithm is deciding the number of employees for the related jobs, it uses before stated total capacities in the system, thus the job orders automatically plan to reach maximum capacity every hour. Also, employee abilities are considered when an employee is selected for a related job.

Some important parameters such as production order date, job order no, and production order priority are taken as a basis while all job orders are planned with production auto schedule.

As shown in Figure 1, the required employee number is planned for all jobs. In Case 1, all employees were assigned optimally to the workstations. At the end of case 1, job 1 is finished and these 2 employees are assigned to job 3 real-timely in case 2. While all these assignments are taking place, employee abilities are considered. Another important point is occurred in cases 6 and case 7. Firstly, in case 6, a number of employees for job 7 is planned as 1 person and the job finish time is specified as 17:30. In case 7, when the number of employees is increased up to 2 persons, the job finish time is updated as 17:00 in real-time, thus real-timely required employees are assigned to the necessary workstations.

As shown in Figure 2, employee assignment occurs to the related workstations as a first process. In this scenario, employees are assigned to the workstation at the beginning of the day and stay constant till the end of the day. All operations in a day are taken as a basis while employee assignment is planned.

As seen in the figure, takt time is specified as 5 minutes, and operations that equal to this takt time are assigned to the workstations. If an operation can not be finished during the takt time, the employee can move to a previous workstation or next workstation to finish the job. As seen between 07:35 and 07:40 minutes, 13B1 and 14B1 operations are assigned to the workstation 4. 14B1 operation duration is too much for takt time and so, some part of this operation is planned to do at the workstation 5. Because of that assigned employee for the 14B1 operation will move to workstation 5 from workstation 4 between 07:40 and 07:45 to finish this job.


Eredmények

Managing production and labor truthfully is going to give gain from the potential loss in production.

MSF allows for managing the production areas properly with an exact production auto-scheduling, thus providing increased production efficiency and flexibility, saving time spent on planning, increasing the production capacity, line balancing, and revealing hidden capacity. On the other hand, as employee management is kept under control with real-time labor auto-scheduling, workload balancing is provided.


Összegzés

Optimally assigning job orders to workstations, managing the employee dynamically and flexibly in real-time, hidden capacity use, planning instant production status change, and increasing production capacity can offer versatile improvements in production. MSF can bring all these enhancements in manufacturing with accurate data and correct resources.

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