| The fourth industrial revolution brings with its significant effects that make existing companies around the world feel the need to migrate their structure and their way of operating.One of the first aspects that is clearly affected in the largest companies is the competitive advantage since day after day new companies are being born which use the latest technologies and are better coupled to changes and industrialization because their structure is less robust and its simpler processes.From the operational part of the industry there are multiple strategies that can be strengthened and that can generate considerable savings in companies and value propositions for end consumers since changes in the operation directly affect the quality of the final product.A clear example of this is maintenance,although this practice has existed in the industry since the first Industrial Revolution and has had different evolutions,companies are not aware of the real benefits of applying correct maintenance plans to equipment and implementing processes aligned to avoid failures and loss of production.Throughout history,some companies such as Ford,Mitsubishi and United Airlines Stanley Nowlan & Howard Heap have tried to improve maintenance application methodologies and have achieved to migrate this practice until that point in which we are already thinking of combining this basic process of the operation with Industry 4.0.Nowadays,the most developed type of maintenance that includes the application of artificial intelligence and machine learning is predictive maintenance,this type of maintenance has important benefits such as: a twenty five percent of reduction in maintenance costs,an increase of twenty five percent in productivity and seventy five percent decrease in downtimes,which is reflected in greater machine time availableAlthough Tetra Pak has been considered the leading company in the cardboard container market for food and beverage packaging(for many years the market share of the market was ninety five percent),in recent years and given the rise of the industrial revolution it has lost thirty five percent of its market share and is strongly threatened by its competitors who have managed not only to copy its machine and product designs but also the services they provide to the end customer.That is why this research is focused on finding a solution to this problem of loss of competitive advantage for Tetra Pak,based on the creation of a new product "PREDICTIVE MAINTENANCE",that can be sold to its end customers and that does not exist in this industry anywhere of the world.Predictive maintenance can be considering the product of the future in the industries because gives a solution that will allow them to identify system failures in advance,avoiding unexpected machine stops,production losses,increased waste and increased operating costs,moreover this product has the ability to combine oldest process with the industry 4.0generating a new perspective of the machines operation.The innovation of predictive maintenance lies in the fact that the operator or supervisor of the production line can maintain continuous communication with the system,identifying in advance possible failures and damages that could affect a production process without having to follow a specific maintenance plan with spare parts life time and specific tasks.But what would be the contributions that this new product can bring to the end customers and for Tetra Pak?With the predictive maintenance product,what the company seeks is to offer its end customers a solution in which they do not have to worry about variables such as the deterioration of their machines to be updating the maintenance plans,as well as to monitor the constant creation of a maintenance plan for their production lines and finally a solution that allows them to have a much higher efficiency and productivity than what they are normally used to.The initial investment that each end customer of Tetra Pak must make to obtain this service will be around 51 K EUR per production line and their return on investment will be reflected in approximately three years,in addition to this,customers can obtain significant savings in their maintenance costs of up to 245 K EUR per line after eight years of use of this new product and can achieve greater efficiency in their production processes.The sales plan of this new service will be based on five steps: correct selection of clients according to segmentation,analysis of the feasibility of implementing the solution in the client,development of the client's maturity analysis,offer to the customer the trial mode and the final selling proposition.The customers to whom the sale of this product will be focused are the same customers who currently buy services and machines with Tetra Pak,nevertheless for Tetra Pak has greater accuracy when it comes to attracting more customers for its new solution,these must will be segmented into three groups: first,the product will be offered to customers with current contracts and on-site engineers,then to customers with current contracts but without an on-site engineer and finally to customers who do not have any active service with Tetra Pak,in addition to this the first offers will be made in the Andean region in the countries of Colombia,Ecuador,Peru and Bolivia and then the product will be offered in the rest of the world.Finally,this new product will bring Tetra Pak considerable benefits,on the one hand,it will not only reposition itself in the market(for being the leading company in this industry in the application of predictive maintenance),but it will earn the trust and loyalty of its end customers again.This project will entail an initial investment of 6M EUR for the company,taking into account that they must make a contract with Microsoft to have access to the Azure cloud for data storage,the development of predictive software,the assembly of the QPMC Quality and Performance Management Center and some specialized consultancy contracts that will serve for the development of the product.The project's internal rate of return for Tetra Pak is expected to be eighteen percent,with a cost benefit of 1.26 and a payback of 3.5years. |
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