With the advent of the Industrial Revolution Fourth, some predict a dark future for the worker in a factory where robots and smart manufacturing machines will replace a man who will be limited to just supervise the operation of the factory of the future.
At present the small scale transformations or trends that will define this Factory of the future are already happening. These technological developments and market trends will define its appearance and operation.
The following table lists some of these trends and the expected positive or negative impact for the role (or lack of it) of the worker of the future.
The negative impact of some of these trends is mainly due to the high levels of automation that are needed to achieve the objectives.
What can we do to adapt to these changes and prevent this revolution run over us? The natural response is to worry and choose conservative strategies to stop this revolution at all cost. There has always been a fear of job loss of with any technological breakthrough. For example, with the invention of the printing the scribes nearly disappeared and the invention of the personal computer put in the hands of anyone the desktop publishing. In other cases, with technological breakthroughs new jobs appeared such as those associated with commercial aviation.
During the different industrial revolutions, the role of the worker has been rather passive in terms of how he assimilated and influenced the transformation of their work. With the First Industrial Revolution, artisan work (manual and customized) became a work driven by coal-based energy and steam. With the Second revolution, the work was divided into simple and repetitive operations that allowed the mass production of identical products. With the Third and subsequent digitization of manufacturing (computers, PLC, CAD / CAM …), the obsession with quality and the elimination or reduction of defects introduced new organizational concepts such as lean manufacturing or TPM that tried to reinforcethe active role of the worker as responsible for the product and not just a gear in a complicated clockwork. However, at present, with the Fourth Industrial Revolution, the progresses in information technologies and the globalization allow us to attend these changes in a more reactive way.
Then, what will be the evolution of the work in the factory of the future? In many aspects, the worker’s role has not changed much since Adam Smith proposed that, as long as the work is divided into operations and paid properly, the matter is settled. However, statistics do not confirm Smith’s premise.
So, what is the recipe to create more productive and healthy environments? It seems that team managers have a large share of responsibility in this regard: recognize the good job, show that their contributions are valuable, provide adequate tools, listen them and include them in problem-solving. In short: to create a trusty environment for open discussion. Simple, isn’t it?
Not so much, one can not fall in the trap and patronize the worker. There is also needed a personal commitment and a change of attitude. Even in monotonous works are examples of motivated and committed employees. In these cases there is a common denominator: people who are not content just doing the tasks as specified in their job description. Hospital cleaning staff that interact and give support to the relatives of the patient, hairdressers that listen to the client or workers who strive to be more efficient and look for improvements that have the effect of reducing the environmental impact of its activities. Increased autonomy and decision-making capacity result in an increased worker satisfaction. So, how to increase the autonomy in a production line? Precisely technological breaktroughs are the answer to this challenge.
Improvements in automation, adding more robots to perform supporting tasks (internal logistics), collaborative robotics which share space securely with workers and data analytics systems that facilitate more effective decision-making, can be seen as threats to the survival of the role of the worker or as opportunities so this role evolve towards a more active position in the revolution to come.
During a recent meeting I participated, where the vision and priorities of the factory of the future was analyzed, various international experts concluded that the role of workers must evolve from a skills focused in the machinery they use (which will be more and more autonomous and intelligent) to become experts in the manufacturing process in which they are working.
How to protect jobs into the factory of the future? One of the recipes will be to provide the workers tools that result in their increased autonomy and decision making so they can perform their job in a highly flexible environment achieving an adeqaute job satisfaction.
Who knows, maybe in the future, each worker could take to work his own robot as a tool. Thus, the workers with the best “trained” or programmed assistant-robot will the ones with an ensured job.
The estimation of a successful manufacturing realization is often linked to the project criteria quality, time and costs. Often it’s not possible to find optimum solutions for all criteria. For example, an exceeding quality leads to higher costs as normal. Thus, a well-elaborated project organization that focuses on a steady work flow and efficient capacity utilization is necessary to realize a manufacturing project successfully. Hence, high competence and extensive project experience are essential.
Production simulation is a very useful tool concerning the possibilities of gains in the process of production and as result, cost reduction. In order to achieve an optimum integration design vs. production, it is necessary to model not only the product but also the factories facilities and integrate them into a single simulation model. Best results are achieved when this model is linked to other optimization systems. The simulation allows finding the best workshop layout and assembly sequence according to the building strategy of the product.
In CARTIF we have experience in implementing the complexity of the production facilities in discrete simulation tools (Witness). The models allow us to ensure optimizationin order to reduce production costs. We have created models for large plants (eg Renault), but also SMEs are benefiting from these advantages. For our purpose the production system can be modelled as a system where the input variables are:
These variables can have a stochastic or a deterministic value. For instance, a timetable can be considered as a deterministic value, whereas the time between failures is a stochastic value.
The main output variables obtained from the simulation are:
Our advice, when we think of improving our productive process, especially if it involves an investment, and we want to measure the final impact, discrete simulation is the ideal tool.
The activity in R&D is very diverse. The results are visible every day, although they need important periods of time in order to bear fruit. Success in this field is the result of a constant effort. Clearly, the maturing period is higher than political mandates, and probably this is the main difficulty in achieving a political consensus.
The Spanish society is not aware that their standard of living is linked to the rate of advancement of science and technology in our country. Therefore, our leaders do not feel any political pressure to avoid the lack of public resources dedicated to R&D. It is as if almost no one is interested in changing this situation. The famous cry of the Spanish writer Unamuno, ‘Let them invent’ is seen as the reflection of suicidal thought of lots of Spanish people.
Here, there are some data of 2014, last released by the Spanish Statistics Institute. The Spanish R&D resources rise to 12.821 million euros, 1,5% less than the previous year. This represents 1,23% of GDP and with this data, we go back to the situation of 2003, a trend that began in 2010. Our position is below the EU average: 2,02%. It is too below Portugal, 1,34%, and far from Germany and the Nordic countries, whose spending is approximately 3% of their GDP. Unlike in Spain, the EU average continued to rise in the year of the Great Recession. The situation is even worse if we compare ourselves with world leaders; South Korea spent 4,04% in 2012, and very near Japan and USA.
Data become more unfavorable if we delve into 2014, because the Spanish Government reduced the resources devoted to R&D by 1,1%, and enterprises 1,8%.
The public sector data are real. The companies’ percentages of the annual survey are made by the Spanish Statistics Institute, following the methodology of the Frascati Manual. However, it could be possible that many companies, for tax reasons or prestige, declare as R&D maintenance expenses and others. There are more circumstances that may affect survey numbers, such as capacity expansions.
There are four regions that increased their R&D spending in 2014: La Rioja, Murcia, Galicia and Valencia. The rest reduced them. In relative value in % of GDP, there is a big dispersion: The Basque Country with 2,03%, Navarra with 1,75%, Madrid with 1,68%, Catalonia with 1,47%, above the national average. A great distance followed by other regions, like Andalucía with 1,03% or Baleares with 0,32%. These percentages show the lack of interest from both administrations, central and regional, in encouraging basic engine of economic and social progress.
Three steps to reduce waste, emissions and the use of resources
“Green Manufacturing” can be defined in many ways, but in this post and the following ones, we will focus on the “greening” of manufacturing, this is, reducing pollution and waste by minimizing the use of natural resources, recycling and reusing waste and reducing emissions.
A growing number of businesses are finding those investments on reducing waste, pollution and the use of natural resources, along with recycling and reusing what was formerly considered waste, yields benefits not only in terms of an improved bottom line, but also in terms of employee motivation, morale, and public relations.
There are individual and collective initiatives with private, public or even both types of funding. One of them, in which I am involved, is the demonstrative REEMAIN project. In this project, supported by the EU 7th Framework Program, we promote innovative strategies on the use of resources (energy and materials) at the factory, including the optimization of the production-process-product, a seamless integration of renewable energy systems and the recovery of wasted energy. This project has demonstration activities in three factories: a biscuit factory, a foundry and a textile factory specialised in producing denim.
Our “recipe” is based on three consecutive steps: first Reduce, then Recover and finally, Replace.
It is also possible to make use of a combined approach to the electric and thermal supplies using co-generation or tri-generation biomass plants (with or without solar panels support). A generation plant attached to the factory produces a fraction or the total of the electricity, hot water (or steam) and even cold water that the factory requires for its operation. These proposals represent a deep impact on the existing manufacturing systems. The installation of the required attached infrastructures and their interconnection with the production systems is a complex issue. In some cases, the implementation of these new systems will require changes in the production planning and management.
In next posts, we will talk about the advantages and the obstaclerace that a factory will have to overcome if it decides to become “green”, or at least, to try.
One of those technologies allows machines to discover by themselves the different states an industrial process features. Imagine a computer repeatedly fed with values generated by the sensors installed in an industrial process. Non-supervised machine learning techniques make possible the computer finds out the sensor data belong to, let’s say, three classes and moreover it characterises the classes. What the computer could not do is to name the classes, unless a human operator provides it a clue. That is what the operator does when he examines the computer outcome and assigns the names starting, stopping and running, just to follow the example. But in spite of this limitation, the non-supervised machine learning can be successfully used to detect faults or malfunctions that have never been observed in the past. This is what CARTIF did in the hydroelectric sets of a hydroelectric power station.
Hydroelectric sets are at the heart of hydroelectric power stations. Its role is to transform the energy stored in the mass of water retained by a dam into electric power. Each set is monitored and hundreds of variables are registered: electric current and voltage, temperature measured in the mechanical elements, in the refrigeration and water streams used for refrigeration, flows of water and air, etc. In our case, we have the values recorded along two years during which no fault was detected, and so we had not information about the possible faults. The challenge was to design an algorithm able to detect faults.
The solution developed by CARTIF is based on the SOM (Self-Organising Map) neural network, which is capable of non-supervised learning. The network was fed with all the available data and she was able by herself of discovering the possible states the hydroelectric set could present. The network labels the states in an arbitrary way and to give the correct names a human operator has to collaborate. However, this is not required to detect faults. Since the data used for training represent all the possible non-faulty states, any network input that does not fully fit with those states corresponds to a fault.
This case can be easily identified by checking the similarity between the sensors signals and the prototypes stored by the neural network. When this similarity is too low, it indicates a fault is occurring.
During testing stage, the algorithm implemented by CARTIF was able to detect an overheating twenty minutes before the plant supervision system raised an alarm. It is important to note that our system used already available sensors and no new ones were required.
So, while we wait for the day machines will rule over us, we may use them to implement intelligent algorithms to improve industrial process supervision with no need for high investments.
Firstly, it is necessary to insist on the fact that, talking about scientific and technical progress is to do about economic and social progress. This is like this since homo sapiens appeared on Earth. But it is absolutely obvious since the late Middle Age, when science started to take off and to apply the knowledge of it to know human needs. The Industrial Revolution took its first steps in the eighteenth century after achieving the use and control of natural sources of energy. Then, the scientific and technological progress has continued unabated. Without it, our lives would be much poorer and the welfare state would be an entelechy.
When so many politicians and all kinds of demagogues filled their mouth promising to improve living conditions of citizens, probably they are not thinking that the basis of their claims, if they really want social progress, is linked to scientific and technical progress.
Unfortunately, we have heard some poor references about this only during the last Spanish electoral processes. It must be that it is a subject without influences on the electorate. This is the first and greatest obstacle that society has to lead in order to start to consider essential that the social welfare is closely linked to advances in science and technology. Opinion makers and those who cause these several opinions have a beautiful but difficult task.
The last major financial crisis, which began in 2008, led to the reduction in research and innovation resources. It is true that they were not the only nor, in the short term, the most painful, but with this reduction is impossible to improve in the short and medium term.
It is necessary that those who govern us and who aspire to do, understand the importance of research and innovation, and try to efficiently undertake the necessary and constant actions to be a social value accepted, avoiding the reduction of these resources.. It is necessary to get a suitable atmosphere for the efficient use of public and private resources, in order to be a richer and more solidary society.
