From this article you will learn:

• What challenges does the automotive industry face?
• How can the right data help improve productivity?
• RTLS technology to support manufacturing and logistics professionals

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The automotive industry accounts for around 8% of Polish GDP and over 13% of exports. It is also one of the main employers in the country. According to the European Automobile Manufacturers Association (ACEA), the automotive industry in Poland currently employs around 203 000 people. The further development of this industry in Poland, which consists mostly of foreign companies, depends to a large extent on the availability of skilled and productive workers. If they are not available, companies will be forced to relocate their production to other countries. Based on surveys of executives and decision makers of domestic automotive companies, the Polish Automotive Industry Association discusses these issues extensively in its 2019 Report entitled. "Automotive Industry Executive Barometer".

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What are the most important issues facing the automotive sector in Poland over the next 6 months

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Automotive Business Managers' Mood Barometer, Report June 2019, Polish Automotive Industry Association

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Fifty per cent of those surveyed are worried about recruiting skilled workers and 44% are concerned about rising labour costs. One way to deal with these concerns is to increase the productivity of employees already in the workforce. Companies can do this by increasing automation or improving the efficiency of current processes in which employees are involved.

The first step to improving productivity is to thoroughly understand existing processes and analyse their potential for improvement. Thanks to the increasing use of information technology in industry (so-called Industry 4.0), manufacturing companies can already rely on real data rather than just observation and experience for this type of analysis.

In carrying out such analyses, ERP class software may be used, used among others for resource planning. This is a very useful tool, but it should be remembered that the quality of the analysis depends primarily on the quality of data used in it. Unfortunately, data on the productivity of individual employees is in most cases residual and often of average quality. Companies now only know when people are at work and, in some cases, at which machines they work - provided that the employee in question actually punches their card. Such data serves more to control the employee than to help understand potential weaknesses in processes, inefficiencies in their work and their role in those processes.

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The right data is the basis for the right decisions

In this article we would like to discuss how the productivity of employees can be improved with the help of a tool which is still little known on the Polish market, namely the Real-time Location System(RTLS). Such systems allow for precise measurement and analysis of the movement of people and objects in indoor spaces. This is made possible by placing small locating devices on the monitored objects, which send a signal to receivers installed on the production hall, which in turn calculate on this basis their exact location in real time. The data obtained is presented, for example, in the form of heat maps or spaghetti diagrams superimposed on a plant map or in the form of indicators describing a specific process. In production plants, forklifts and logistics trains are most often monitored in this way, but the best results can be achieved by analysing the work of the most valuable resources used in production processes and internal logistics, i.e. employees. In this way, you can find out, for example:

• how many people, when and for how long are actually involved in each stage of the production process,
• what differences there are in employee activity during different shifts (and there certainly are!),
• how much time an employee actually spends in the work zone and how much time is wasted on, for example, fetching semi-finished products from a distant warehouse.

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Any Lean cell would be delighted to have this kind of reliable data, especially if its acquisition does not involve the need to slog around with a stopwatch and a piece of paper to make measurements. Even such simple data can be very helpful in reducing waste (Muda). And it doesn't stop there. Even more interesting information can be obtained by combining data on the movement of employees with data on the movement of other mobile resources involved with them in production or intralogistics processes:

• flows of work in progress between successive production centres,
• the route and stops of the logistic train,
• the location of mobile means of production,
• transport trolley routes.

This type of aggregated information helps to better understand the entire process and, on this basis, identify inefficiencies and plan corrective steps. This could be a better allocation of employees to tasks, a decision to provide additional training to employees with lower productivity, or changes to the organisation of processes to, for example, eliminate unnecessary employee movement. Decisions based on hard data have a much lower risk than those made solely on the basis of observation.

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Setting new productivity standards

The next step after carrying out corrective actions is to understand how they have actually affected overall productivity. Production and internal logistics processes are an interconnected system, and many of these connections are not at all obvious. It is therefore worth comparing the figures before and after corrective action.

In the long term, the role of RTLS solutions should be to support production and logistics managers in planning. This is made possible primarily by the ability to establish process standards or indicators, based on real data, and to subsequently monitor whether processes are running as planned. Real-time monitoring of resources makes it possible, for example, to establish and observe:

• production time per outlet,
• the operating cycle of a logistics train,
• the minimum or maximum number of employees at any one time in the selected zone.

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RTLS can provide real-time information on deviations from standards via SMS notifications, email, or a screen placed at the production line, allowing for a quick response when needed. In addition, cross-sectional analysis reports can provide useful information for resource planning, for example:

• to assess the current level of staff work organisation and productivity,
• identifying opportunities and conditions for optimisation in a specific process or for a specific team/employee,
• monitoring changes in employee performance in response to Lean cell experiments,
• assessing the actual need to employ more staff for increased production.

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Summary

Employees are, and will long continue to be, an essential resource in manufacturing. Given the problems in securing suitably skilled workers in the automotive industry, it becomes all the more important to ensure that the productivity of those already employed is optimised. Introducing new work standards based on actual employee activity and habits can help detect inefficiencies and wasted motion/time and understand how the entire production process can be improved by improving employee productivity.

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Would you like to find out more? Visit the Indoorway website or email us at indoorway@aiut.com.