In the era of absolute digitalization and changes in consumption patterns, logistics has embarked on a race for productivity, which translates into a constant concern for responsiveness.
Faced with ever more demanding and versatile customers, delivering quickly, qualitatively, quantitatively and responsibly seems to be a constant challenge. The company must be able to offer ever more references, in sufficient quantities, to trace its operations in and outside the warehouse...
Whether we call it “Supply Chain 4.0”, or even sometimes 5.0, it doesn’t matter! What we can see is a strong desire to adapt the Supply Chain to its environment in an atmosphere of technological but also societal revolution. The mechanization, automation, and robotization of logistics processes are an underlying trend where machine learning, artificial intelligence, vision systems and even IoT represent important levers of innovation. These new practices are making significant progress in terms of efficiency while controlling resources, production rates and the overall productivity of logistics platforms.
Adapting to stay competitive: that’s the goal of every business! But with what tools? What place for humans in these mutations?
Mechanization, automation, robotization: what uses? What complementarity?
Improving performance and limiting arduousness are the two main goals associated with the invention of tools and machines. Symbolic of the first industrial revolution, the primary goal of mechanization is to replace human force by helping, in particular, to move or carry heavy loads, to limit travel, and to increase output while reducing the physical impact on the operator.
Warehouses are being driven to mechanise by the increasing volume of flows and the need to manage a large number of items. Mechanisation is an effective solution for carrying out repetitive tasks in a shorter time. It can be found in warehouses using pallet trucks, forklift trucks or simple conveyors.
From the point of view of productivity, mechanization will make it possible to gain efficiency by supporting the work of operators and supporting human work.
Automation: when the machine becomes intelligent
Automation is described as " making a process automatic, making it work on its own” [1] (implied, without human intervention). This is where the difference lies: it adds to the mechanical system the ability to carry out autonomous tasks. This capacity can be primarily physical, such as for packaging machines or stacker cranes, but also IT. In the latter case, the system integrates the notion of intelligence and decision-making, based on algorithms, which allows it to answer to constraints, criteria and goals.
In the logistics context of the warehouse, it can be used to address issues such as the best way to carry out a sequence of picking tasks, to determine the optimum picking path or the best storage location, or even the best bin for carrying out an order, etc. In the warehouse, it takes the form, for example, of optimised order release solutions, or flow synchronisation on goods-to-person systems.
Its ability to generate data essential to understanding what is happening in the warehouse, supervising and tracking activity makes automation an essential source of data. Real-time progress of order preparation, performance indicators, production counters, etc., all data that can be used for the purposes of rationalization, improvement of productivity but also forecasting, in terms of maintenance for example. Although many execution and management actions remain human, the generalization of automated processes in a warehouse requires a global supervision system, capable of providing detailed information on the progress of the activity and the performance of the equipment.
Robotization: the ultimate level of evolution
Robotization can be defined by the action of robotizing, of introducing the use of robots into a structure. A 100% robotic logistics process is a completely autonomous process, without human intervention, both in physical operations and in the organization and synchronization of flows. Robotization is thus the ultimate degree in the evolution of mechanization and automation since it provides even more flexibility than simple automation, both in terms of physical actions and intelligence:
- In terms of physical actions, the robotization of retail picking operations, or even the palletizing of heterogeneous loads, are complex actions which are already or will eventually be replaced by autonomous robots.
- On the intelligence side, the possibilities offered by machine learning allow decisive contributions in activity forecasting, the allocation and organization of resources, or even in predictive maintenance operations... thus replacing the experience of the teams.
With robotization, the role of humans is that of supervising the progress of the activity, maintenance and correction actions of the system, and management of anomalies. The robot thus carries out painful and repetitive tasks, whether physical or intellectual, at high performance rates, allowing humans to deploy their added value in analysis, decision-making and strategy. Indeed, nothing replaces human reasoning and decision-making in particular contexts, in the face of urgency or the unexpected.
And tomorrow?
Behind the notions of mechanization, automation and robotization stand 3 goals:
- answer to the essential “customer promise” who wants everything as quickly as possible and in the best conditions
- make the warehouse a center of efficiency, productivity and quality
- increasingly reduce the strain on operators
These three goals are positioned on three temporalities: learning from the past (by analyzing data and drawing conclusions), making the present efficient and productive (preparation path, etc.), and anticipating the future (predictive maintenance, forecasting stocks, anticipating orders, resources, etc.).
In a context of increasing capacity for field data analysis, process modeling and simulation, logistics innovations will be driven tomorrow by two major levers:
- The ability to report very precise operational information in real time, from the temperature of a component to the geolocation of mobile equipment. This digital intelligence embedded in all processes allows the automated warehouse to generate and return information, to provide even more support for decision-making and contribute to increasing the service rate.
- And it is particularly through Machine Learning that it will be possible to analyze and exploit this data to get the most out of it. Its algorithms have the particularity of learning in iteration based on the analysis of the past and present to deduce the future. At Savoye, we are convinced that the Supply Chain is an ideal area for the application of Machine Learning, on subjects such as resource planning through load forecasting, anticipation of shortages in picking and optimization of replenishment, or even anticipation of maintenance actions on equipment.
The supply chain at the crossroads of changing consumption patterns
Even if they represent different stages of evolution of a logistics process, the functions of mechanization, automation and robotization are completely complementary and can each find their place in a warehouse, depending on the volume of flows to be processed and the logistics profile of the activity. For example, for retail preparation activities, mechanization via picking stations is very relevant for a small number of high-rotation references, while a goods-to-person or even goods-to-robot system will be much more productive for all medium and low turnover items.
If a person can control a simple intralogistics installation, because it can be understood in its entirety by a human, complex installations will require “intelligent” systems to help humans control them.
The supply chain in general, and intralogistics in particular, are currently in a state of flux, at the crossroads of changing consumption patterns and technological advances. As a veritable distribution factory, the warehouse must combine performance, service levels, land optimisation, scalability in the face of growing flows and responsiveness in the face of ever-increasing delivery constraints.
While automated and robotic solutions have become essential in meeting these challenges in just a few years, the next 10 to 15 years promise to bring further major breakthroughs.
About Savoye
Savoye is an international player in the design and integration of equipment, IT solutions and automated systems for logistics centers. Savoye designs, manufactures, integrates and implements solutions (automated equipment and software) and tailor-made logistics services capable of responding to all Supply Chain processes. Savoye relies on the synergies and expertise of strong brands recognized in France and internationally: A-SIS, brand of the publisher of LOGISTICS MANAGER SUITE, complete suite of OMS, WMS, WCS, TMS and EDI software solutions for Supply Chain; INTELIS, brand of the designer, manufacturer of mechanized and automated systems for light or heavy loads: order preparation, mechanization of shipping packaging, automated storage; and PRODEX Brand of the manufacturer of dynamic storage equipment and handling systems. Savoye employs 630 employees and achieved a turnover of 90 million euros in 2018.
[1] Source: Universalis encyclopedia
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