Optimization of researcher shifts with consideration for COVID-19 infection control

Overview

With the outbreak of COVID-19, we used an annealing machine to create shifts for our researchers under constraints that took into account the newly created risks of infection.

What we want to solve

With the unprecedented outbreak of the infectious disease, the researchers were required to work under new constraints which did not allow for overcrowding. To ameliorate this issue, the researchers were divided into separate shifts to allow the continuation of their work.
We decided to set restrictions on the number of people who could work a shift. For example, for a large room that houses several departments, we set a limit on the number of people who could come to work across multiple departments. We also set different conditions for personnel working in laboratories, depending on the size of each laboratory.
Even though more than 30 departments share the same building, there was no mechanism to manage work restrictions across these departments.
The work schedule for each research topic was also in flux, with readjusting shifts being required in such high frequency.
In addition, because many different teams use the laboratory, if prior arrangements are not made properly, experiments cannot be conducted even if a person comes to work if he or she has a conflict with a member of another team. These issues made the coordination process very complicated. Forcing the researcher or department head to make these sorts of adjustments distracted them from their main tasks.

Current Issues

• Time consuming to create and coordinate shifts
  Because there were many departments and researchers, each with their own set of requirements and needs, creating and coordinating shifts was no easy task.
• Difficult to catch up with urgent requests
  Researchers make schedules in advance, but depending on the project's progress, they may make a special request to use the laboratory on much shorter notice. On the other hand, there are also cases when researchers withdraw their reservations due to a delay of a project's progress or due to illness. Because scheduling a shift takes time, it is difficult to manually reflect such an impending situation.
• May deviate from the actual situation
  There were instances where the laboratory was scheduled to be used by one group, but then quickly abandoned and unused. And in some cases, the laboratory was shared by disparate groups which were not on the schedule. This lack of control could have resulted in problems with infection control measures.

Toward a Solution

We collected the following information and used an annealing machine to compute the optimal combination of researchers' work schedules that satisfied various constraints, thereby automating the creation of researchers' shifts.

Information required for optimization

• Schedule of laboratory use requested by the researcher
  We collected information on who would like to use the room, when, and which room they would like to use.
• Laboratory Equipment and Number of Rooms
  Since the experimental equipment differs from room to room, we set the number of rooms per equipment.
• Days of the week and times when researchers can come to work
  To meet restrictions and conditions while maintaining equality, we collected requests for days and hours of work.

Constraint

We have set a limit of up to 30% of the normal capacity of each laboratory or rooms.

Interactions to consider

• Compatibility between researchers
  Productivity could be affected by the combination of researchers in attendance.
• Maximum stay time
  Productivity was affected when operating hours in the laboratory exceeded a certain level.

Changes after introduction

Fixed shift placement

Ideal shift placement

There had been no mechanism to manage attendance across departments, but it is now possible to organize shift work for the hundreds of people who work at the institute.
Our solution can create shifts on a weekly basis, making it possible to accommodate requests to come to work with as much consideration as possible for the researcher's research progress and family circumstances.

Related Links

Work Shift Optimization Solutions: Financial Solutions:Hitachi (hitachi.co.jp)

The "Work Shift Optimization Solutions" uses Hitachi's calculation technology to create optimal work shifts that balance the needs of management, inquiring customers, and operators of companies operating call centers.

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