Every employee-executive level and above, who walks into your factory, carries a resume which details his/her knowledge and skills acquired over the years. Do your sewing workers or spreading helpers also carry a similar resume? Why not? Because hand skills are often acquired on-the-job and certification is not considered mandatory. Even the Government and private run sewing machine operator (SMO) training programmes offer only a qualifying certificate (to successful trainees) without detailing the micro-skills attained. Every organisation today has a separate department for digitalisation which might be named as Manufacturing Excellence, Advanced Manufacturing etc. The intention is to automate/digitalise or reduce human error/dependency. In his earlier article, Prabir Jana explained the tech map of the sewing floor, and in this article, he explains the roadmap to digitalisation of the sewing process.
The sewing workers constitute 80 per cent of the total production workforce in any manufacturing organisation but we still know very little about them. Similarly the sewing process constitutes around 80 per cent of the total manufactured time in any merchandise, yet we know very little about these operations. What skills are involved in these? The challenge of digitalising sewing starts here.
The existing approach of maintaining the ‘skill matrix’ which actually lists operation name against operator name is faulty. While we loosely use the word ‘skill’ in place of ‘operations’, we have to understand and acknowledge that ‘skills’ and ‘operations’ are two different things. For example, ‘pocket attaching on shirt front’ is an operation name, but one of the generic skills required to excel in this operation is the ability to ‘sew short bursts with precision stop and pivot’. While the number of operation lists can be infinite (with newer styles added to the database every week), the number of generic skills are limited. We need to shrug off the age-old ‘skill matrix’ in favour of the new-age ‘generic skill matrix’ which is the first step towards digitalisation of the sewing process.
Once every sewing operation is converted to generic skills (which may be numbered Skill1, Skill2 and so on), every garment style can be converted into a generic skill map as shown in figure 1.
Once the styles are digitalised, the operator’s skill matrix has to be similarly digitalised. There are a finite number of generic sewing skills for different types; every operator evaluated for one or more machine types and generic skill rating are expressed in numerical value. Figure 2 shows how each sewing operator can be digitalised.
Figure 2: Digitalisation of Sewing Operators
In a truly digitalised smart factory, every style can be converted into a generic skill map (Figure 3) and every sewing line can be converted to generic skill map. Now both the target (digitalised style) and the resource (digitalised skill matrix) can interact with each other through software programs (without manual intervention) and automatic allocation can happen (Figure 4).
Figure 3: Every Style is Converted to Generic Skill Map
Figure 4: Automatic Allocation of Sewing Operators to Sewing Operation
It is important to note here that I have used the word ‘digitalisation’ as there is a subtle and important difference between ‘digitalisation’ and ‘digitisation’. The traditional approach of simply converting existing analogue records (data/text/picture) to digital may digitise your factory, but won’t make your factory smart as those will be just islands of digital records but they will not be able to talk to each other. To enable one dataset to talk to another dataset, intelligent digitalisation is the way forward.