Modern industry is characterized by the use of machines in production processes. These machines, increasingly sophisticated and precise, allow increasing productivity and reducing production times. However, the interaction between the operator and the machine can generate interferences that negatively affect the efficiency of the process.
In the business world, it is common to think that productivity increases if the same operator is in charge of several machines. However, as I mentioned, this can generate interferences that negatively affect production. Therefore, it is important to conduct a study of man-machine interference to determine the number of machines that a worker can handle without the use of one interfering with the production of others.
Let's imagine a precision watch factory. Inside, an army of operators is busy assembling and adjusting the delicate mechanisms that will give life to the hands of time. Each operator is in charge of several machines that perform different tasks: cutting, polishing, assembly, etc. Each machine has a determined cycle time, that is, the time it takes to perform its task. However, machines are not autonomous beings; they need human intervention for their correct operation. This is where interferences come into play.
In this article, we will delve into the fascinating world of interferences in work with machines.
What are Man-Machine Interferences in Work with Machines?
Man-machine interference occurs when an operator has to attend to several machines at once and some of them are left unattended because their operation cycle ends at the same time. This can generate stops in production and a decrease in efficiency. Interferences are these additional times that occur when attending to several machines at once. These waiting times are part of the work method and must be taken into account when calculating the productivity of the installation.
Methods to Calculate Man-Machine Interference
There are three classic methods for calculating interference, based on queuing theory —the Ashcroft tables, the Dale-Jones abacus and the Wright formula— and two complementary tools for studying it case by case: the man-machine diagram and simulation.
Ashcroft Tables
- They are used mainly when the machines attended by the same operator are not identical and the production lost to simultaneous stoppages must be quantified.
Steps:
- Calculate the cycle time of each machine.
- Look up the interference factor in the Ashcroft tables for the number of machines and the relationship between cycles.
- Multiply the interference factor by the largest cycle time to obtain the interference time.
The Dale-Jones Abacus
- It is used to obtain the percentage of interference on machine time, crossing the operator's service time with the number of machines attended.
The Wright Formula
The Wright formula is used to calculate interference in systems where one operator attends to several machines. Interference is the time during which a machine cannot be attended because the operator is busy with another. For systems with six or fewer machines, an empirical graph is used from which interference is read without the need for calculations; for seven or more machines, the Wright expression is used, which we see later with a complete example.
Man-Machine Diagram
Allows graphically visualizing the interference between the operator and the machines.
Steps:
- Represent the work cycle of the operator and each machine in a diagram.
- Identify the waiting times of the operator and the machines.
- Calculate the interference time from the waiting times.
Simulation
It is used to analyze man-machine interference in complex systems. It allows evaluating different scenarios and testing different solutions.
Next, we explain how to use each of them.
Ashcroft Tables: Calculation of Time Supplement for Synchronized Stoppage
The Ashcroft tables come from the work of H. Ashcroft, “The Productivity of Several Machines Under the Care of One Operator” (Journal of the Royal Statistical Society: Series B, 1950), which applies probability concepts to quantify how much production a group of machines loses when a single person attends to them: if two machines stop at the same time, the second must wait for the operator to finish attending to the first. The method is based on the concept of effective number of machines (the Ashcroft number): when the machines are identical, the effective number matches the number of machines attended.
The procedure is as follows:
- Calculate the cycle time of each machine, distinguishing the running time and the operator’s attention time.
- Determine the effective number of machines (for identical machines, equal to the number of machines).
- Look up the corresponding interference supplement in the tables and apply it to the machine cycle to obtain the total time the operator takes to attend to all machines, including waits.
Let's look at a practical example (illustrative example, built to illustrate the procedure). Suppose five identical machines, each with a capacity of 100 pieces per hour of operation, and that for each hour of machine operation there are 0.20 hours (12 minutes) of downtime due to external intervention by the operator. The calculation works out as:
Each machine produces for 48 minutes of every hour of attendance (60 − 12 = 48 minutes), that is, 80 effective pieces per hour per machine.
The operator’s attention takes 12 minutes per machine per hour: with five machines, 5 × 12 = 60 minutes of attention per hour. The operator is busy 100% of the time.
With the operator at full capacity, every time two machines need attention at the same time, one of them waits. Interference is unavoidable and the actual output of the installation falls below the theoretical 400 pieces per hour (5 × 80).
The exact supplement to apply is read from the Ashcroft tables according to the number of machines and the relationship between their cycle times. The practical conclusion is that adding machines to an operator who is already at 100% of their attention time does not increase production: it reduces it through interference, unless the interventions are shortened (preparing tooling and material before the stoppage) or part of the attention is automated.
Dale-Jones Abacus: Calculation of Interference Percentage on Machine Time
Another method to calculate interference is the Dale-Jones abacus. It is based on the concept of service time: the percentage of time the worker dedicates to each machine in each cycle, both internal work (performed while the machine is running) and external work (with the machine stopped). To use it, first calculate the service time and then cross the corresponding curve with the number of machines, obtaining the percentage of interference on machine time.
Let's look at a practical example (illustrative example, built to illustrate the procedure). Suppose a process operated by one worker with 8 machines, with a service time of 8% on each machine and no internal work. Crossing the curve for a service time of 8% with the number of machines (8), the abacus gives an interference percentage of around 16.5% of machine time. This percentage is applied to machine time, not to cycle time.
In productivity terms: if the eight machines each need one hour of machine time, the operator will need 8 × (1 + 0.165) = 9.32 clock hours to attend to them all, versus the 8 theoretical hours without interference. The difference (1.32 hours over 8) is the productivity loss of the installation: 16.5%.
Wright Formula: Calculation of Interference in Percentage
The third method to calculate interference is the Wright formula (Wright, Duvall and Freeman, 1936). It calculates interference as a percentage of the operator’s average attention time and is used when there are seven or more machines; for fewer machines, the empirical curve graph is used. The expression is:
I = 50 × [ √( (1 + X − N)² + 2·N ) − (1 + X − N) ]
Where:
- I is the interference, expressed as a percentage of the operator’s average attention time.
- X is the ratio between the machine’s average running time and the operator’s average attention time.
- N is the number of machines.
X must be greater than N − 1 for the attention load to be viable; if it is lower, the operator cannot attend to all the machines and the problem is one of capacity, not interference.
Example of Man-Machine Interference Calculation
In a machining factory, one worker is to be assigned three identical milling machines. Each machine takes 30 minutes to make the part automatically, and the operator intervenes for 1.5 minutes per part to load and unload it. Deburring the part (1.5 minutes) is done while the machine is running, so it does not stop the cycle. The maximum interference allowed by the method is 10% of the attention time.
The data for the formula are:
- X = ratio between the machine running time and the attention time: 30 / 1.5 = 20.
- N = 3 machines.
Substituting: I = 50 × [ √( (1 + 20 − 3)² + 2·3 ) − (1 + 20 − 3) ] = 50 × [ √330 − 18 ] ≈ 8.3% of the average attention time.
Although the empirical graph is normally used when there are fewer than seven machines, the formula gives a valid approximation in this case. At 8.3%, below the allowed 10%, the operator can take care of the three milling machines: the overlap between attentions exists, but it is acceptable. If the X ratio fell —for example, because the parts require more intervention— interference would grow quickly and the number of machines per operator would have to be reduced or the attention time shortened.
How to Minimize Interferences in Work with Machines
To minimize interferences in work with machines, it is important to design production processes in a way that reduces the operator's waiting time. One way to do this is to increase the number of machines in charge of each operator, so that waiting time is reduced. However, this can have a negative effect on the quality of work and the well-being of the operator. Therefore, it is necessary to find a balance between productivity and working conditions.
Another way to minimize interferences is through the automation of some tasks, which reduces the need for human intervention. To measure the attention and cycle times that feed these calculations on the shop floor, time study with an application like Cronometras and work sampling with WorkSamp cover the two required measurements. Additionally, it is important to perform preventive maintenance on machines to avoid unscheduled stops and reduce downtime.
Conclusion
As we have seen, interferences are an important factor to consider in work with machines. The three calculation methods we have presented allow quantifying the impact of interferences on productivity and help design more efficient production processes. However, it is important to remember that productivity is not everything and that working conditions and the well-being of the operator are fundamental aspects to consider in any production process.
Working with machines is a complex art that requires careful planning and a balance between productivity and working conditions. Interferences are a constant challenge in this art, but also an opportunity to improve the efficiency and quality of work.
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