Lean 4.0: operational excellence supported by digital transformation

The manufacturing sector has been immersed in a digital transformation towards the Fourth Industrial revolution several years. The latest technological advancements allow the whole value chain to be more efficient but focus should also be placed in factories and industrial processes, the real protagonists of this change, and how they achieve this transformation while remaining competitive and profitable in a more and more demanding market.

Lean Manufacturing: what it is and what is its purpose

The lean methodology or philosophy, of wide use in the manufacturing sector, originates from several innovations and techniques to continuously optimize and improve production, while minimizing waste. Traditionally, its origin has been attributed to the Toyota Production System (TPS), initially established by Eiji Toyoda and impulsated years later by Shigeo Shingo and Taiichi Ohno.

The TPS is mainly based on two basic concepts: jidoka, which implies avoiding defective products by stopping production whenever a problem appears; and Just-In-Time, a concept that implies producing only what is needed, when it’s needed and in the amount needed according to customer’s demand. It’s worth noting too that this system contemplates as a key point people involvement, respect towards them and their essential contribution in the continuous improvement process.

The lean term, was coined in the late 80’s by John Krafcik, although the concept has been developed in more detail by James Womack and Dan Jones, years later [1]. In their book, they recommend that all managers or directors that want to undertake a lean transformation in their companies have to think mainly in three business aspects:

• The purpose. Identify customer’s problems and their needs to focus business activities towards the creation of a perfect value for them.
• The process. Implies thinking how the company is going to ensure that each step and decision taken delivers value, eliminating what is not needed and connecting all steps by the flow, demand and production leveling.
• The people. Ensure that all team members are completely involved in the processes, actively participating in their revision and improving them continuously.

Lean 4.0: first the systematic, then the system

In recent years, a new paradigm that aims to achieve operational excellence from digital transformation has arisen: Industry 4.0. Through the application of key enabling technologies, the manufacturing industry can improve its productivity and efficiency, obtain a bigger knowledge from their processes and generate new business models supported by digital tools. But, can Industry 4.0 and lean coexist? The answer is yes, provided that these innovative technologies are applied when and where they make sense.

As in pure lean manufacturing application, in order to decide the application of 4.0 technologies, a waste elimination approach should be taken while taking into account the principles established by Womack and Jones in Lean Thinking. It is very important in this case to avoid creating one of the seven wastes (or muda), over-processing, that is, performing extra activities that are not needed. In this case, this waste may appear while including technologies that are not needed and don’t provide value. Besides, each problem must be adequately analysed, due to the existence of simple solutions, even non-technological, that can solve it.

At Gradiant we work in several use cases where these technologies can be applied in conjunction with traditional lean manufacturing, for example in real time plant monitoring, product quality prediction or demand and raw materials prediction. In the first case, monitoring process data in real time, combined with a variety of algorithms, allows to support decision making and continuous improvement with reliable and exact information, guaranteed by a totally secured communications architecture. Regarding quality processes, their automation through the prediction of product specifications from historians and machine parameters, or anomaly detection, allow to apply jidoka in advance and stop production if a quality problem is predicted, besides detecting the cause immediately. Also, applying prediction algorithms to determine product demand helps leveling production, adjusting and optimizing stock, as well as purchases to providers.

In summary, the digital transformation process and application of new technologies in the shop floor must be based in an action plan previously established and with clear and gradual stages. Each step must be validated through pilots and KPIs that enable fast detection of benefits and disadvantages. Thus, new technologies implementation, business strategy and value provided to the customer will completely fit together.

References

[1] James P Womack, Daniel T Jones, Lean Thinking

Article originally published in Spanish in: https://www.gradiant.org/blog/gradiant-lean-industria4-0/