After seeing the importance of having work standards in all our activities, and the importance of practicing Job Observation by Managers of the company and/or the Workshop, we are talking now about the management of people’s competencies, their training, and their polyvalence, so we can get to the point where:
We implement the “3-stage training” of standards to all stakeholders using the “I do, we do, you do” technique.
We define the operational requirements of each process/activity and the competency levels of each person.
We prepare polyvalence plans in anticipation of the company’s needs, the Polyvalence Matrix.
The 3-Stage Training
From the Standardization management tools and in particular digital work instructions, it is essential to ensure the training of workers for all required activities.
It is of great responsibility to ensure such training, therefore, it is a fundamental task of the team leader (Team Leader or Group Leader).
According to specialists in cognitive psychology, we are able to understand and retain:
10% of what we read
20% of what we hear
30% of what we observe
50% of what we observe and hear
70% of what we say
90% of what we do
On-the-job training is an act of strong management, carried out by the hierarchy of the person being trained. To ensure maximum effectiveness of the training, the following ritual should be followed to ensure I do, We do, You do:
1.- Training Preparation:
Make sure that the training meets a need identified in the Polyvalence Matrix and linked to the person’s current competencies
The trainer (Team Leader) performs the operation himself (or with the support of a senior operator) to remember the operating method
Verify that the standard (work instruction) is understandable and up-to-date
Ensure that the quality requirements are in proper working order before moving on to the next position
Check The station is in accordance with its reference state: available parts and tools, safety features, etc…
Note: it may be possible to prepare the training on a mock-up simulating a workstation.
2.- I DO
The Team Leader does the operation:
Explain the operation to the person trained:
Say which operation is to be executed
Identify the person’s existing knowledge of the operation
Explain the importance of the operation
Ensure that the operator is well positioned to hear instructions
Present the parts, tools, and machines to be used
Show how to perform the operation:
The Team Leader must carry out the operation himself (or with the support of a senior operator), scrupulously respecting the standard, highlighting the main steps, the key points, what is forbidden and why, and what to do in case of anomalies
3.- We DO
The Team Leader must make the operator do the operation, remaining at his side:
Have the operator perform the operation, repeating the main steps, the key points, and the reasons for the key points in a loud voice
Immediately correct any deviation from the standard operating mode
Repeat until the operator has completely memorized the operation
4.- You DO
The Team Leader must let the operator go it alone, and ensure follow-up:
Ask an experienced (senior) operator or the Team Leader to supervise the beginner operator
Encourage the operator to ask any questions, and confirm that he/she knows who to contact for this purpose
Leave the operator to do the operation alone
5.- End of Training:
Organize the follow-up of the beginner operator by a senior operator to ensure that no error leaves the workstation
Verify that the operator always respects the work standard, knows the key points and their reasons, keeping the target time of the operation
The Team Leader must update the polyvalence matrix (ILUO) with the accreditation of the new operator
The operational requirements of each process
The need to ensure the activities in all workplaces requires us to establish a set of criteria, in which we can detail the operational requirements, for example:
Process: Designation of the activity: Positioning parts on tooling
Operation: Performed by the operator or by machine: Correct adjustment or positioning
Standard working conditions: Positioned according to standard form (work instruction)
Quality assurance features: correct functioning of the proximity sensors
Level of difficulty of the operation: A, difficult operation, B, moderately difficult operation, C, easy operation
Estimated learning time of the operation: 1 day, 1 week, 1 month, etc…
Basic knowledge required: e.g. general electromechanics, FP1
Technical skills acquired: skill level, knowledge of the machine, tooling, adjustments, etc…
The Polyvalence Matrix (ILUO): ask experts
Polyvalence is essential to guarantee Quality, Customer Service and to contribute to solving the impacts caused by absenteeism.
The Multipurpose Matrix (ILUO), allows the team leader to know, anticipate and plan for the development of your team’s competencies based on the needs of the processes:
The matrix, in addition to showing us the current state of the training of the entire team, serves as a training planner. It is a tool at the service of the team leader and managed by him. It allows him to formalize the level of competence of each operator on the standard of each position, according to 4 levels of maturity:
It should always appear:
Time frame, case of planning
Three levels of maturity of an operator in a job are defined: I, L, U and O:
I: Is capable of executing the standard operation in the defined time, under normal conditions, and following the instructions
L: It is capable of executing standard operations autonomously, including anomaly treatment
U: Is capable of instructing others in the standard according to the 3-step training method, as well as proposing improvements
O: Train the trainers
In addition, in the Matrix we will make appear:
The incumbent of each position
The planned date of training or change of level (planning mode)
EXAMPLE mlean matrix
H3 Simple and digital implementation of the Multipurpose Matrix (ILUO):
In our long experience, the implementation of the Matrix (usually in Excel), has serious management and updating difficulties. We understand that it is necessary to make life easier for team leaders (it is their responsibility), who are already burdened with administrative tasks.
Every company has a unique way of carrying out its operations. But all of them face one common challenge; the need to connect and access real-time data. Businesses must make fast, effective decisions to remain relevant in the rapidly changing industrial economy.
And connectivity is the game-changer.
Thus the need to adopt industry 4.0 processes. Smart manufacturing is not just about digitizing your factory process. It also revolutionizes the whole business operation and growth.
Let us look in-depth at industry 4.0 and how the technology can help you solve modern business challenges.
Industry 4.0 definition
Industry 4.0 is the fourth revolution that is occurring in manufacturing. In this revolution, the manufacturers are using the computers introduced in the third generation to revolutionize processes.
Industries are integrating new technologies throughout their manufacturing processes. In smart manufacturing, technologies such as cloud computing and analytics, Industrial Internet of Things (IIoT), and machine learning are taking over the daily manufacturing operations.
History of industry 4.0
Since the 17th century, industrialization has been undergoing key developments. In total, four key evolutions have taken place over the years.
The first industrial revolution took place in the early 17th century. In this development, manufacturing processes evolved from manual and animal labor to water and steam power engines.
The second industrial revolution was in the early 20th century. This phase saw the introduction of electricity in production factories. In addition, factories began to use steel to improve the efficiency and mobility of machines.
During this phase, modern mass production concepts like assembly lines and conveyor belts took form. Thus, industries experienced a boost in production with lower production costs.
The third industrial revolution started gradually in the 1950s. In this phase, manufacturers began introducing more electronically aided machines in production. Eventually, manufacturers slowly integrated computer technology into factory processes. Hence, industries began experiencing a shift from analog to digital operations.
In the past few decades, computer technology has almost entirely taken over the industrial process. A fourth industrial revolution, known as industry 4.0, is emerging. Industry 4.0 has taken smart machines and interconnectivity to a new level.
The industries are adopting robotics, embedded software, and advanced sensors in data collection. Industry 4.0 processes also combine the created data with the current ERPs, continuous improvement software, and supply chain to create a new level of forecasts and production visibility. But the truth is that it seems we are forgetting who is making all this evolution happen, people.
Benefits of industry 4.0
But Industry 4.0 spans throughout the entire production cycle. Company employees get real-time data in every production stage, from factory processes, shop floor management to supply chain procedures. Below are some benefits you can benefit from adopting an industry 4.0 digital approach in your company.
Industry 4.0 digital technology uses evidence-based information in decision-making. Level four smart factories also take some of these decisions off your shoulder by providing all the options available where AI plays and will play in the future a key role.
You do not have to worry about decisions made under pressure with machines at work. Every action relies on real-time data analysis and the current trading environment. The technology can also detect significant problems in assembly lines before they occur. Thus, all maintenance plans are proactive, ensuring that factories do not suffer downtime due to breakdowns. Do not forget that all the data can be gathered by machines but also from the broad knowledge base made by the workforce. Again behind any action, there is always people.
Optimize the supply chain
A connected supply chain identifies priorities and adjusts its operations to accommodate them. It also processes new information and adjusts accordingly in case of emergencies. For instance, if shipment delays due to unavoidable circumstances, the supply chain adjusts the mass production settings and modifies the manufacturing requirements.
The smart factory uses various technologies to cut costs and maximize profits while retaining quality. For instance, shipping yards now use autonomous equipment and cranes to streamline offloading operations. Also by using digital tools to manage the shop floor such as standards, actions, audits etc….will reduce considerable the costs of non-quality, and the waste of not doing the things right from the beginning…so robust standards to our work force are key to cut costs.
Also, robots are nowadays available at affordable prices and in different sizes. Autonomous robotics support manufacturing by moving things around the factory space. Besides maximizing floor space use, robotics also cut labor costs. Also, robots do not suffer from fatigue. The factory operations can run for hours without the need for a break.
Again the perfect recipe is a combination of automation and people with the right tools.
Industry 4.0 digital transformation processes help manufacturers optimize the assets at every production stage. The Industrial Internet of Things (IIoT) and digital twin give the in-charge personnel visibility of the resources from any part of the world. Asset transfer such as purchase and sale of stock is streamlined and managed in a central location.
What defines a smart factory?
A smart factory is a digitized production facility. It uses factory machinery, connected devices, and production systems to collect and share data between people and processes. A smart factory is empowered by digital transformation technologies such as the Industrial Internet of Things (IIoT), big analytics, edge computing, AI and cloud computing. Smart factories combine the digital and physical worlds to monitor mass production and again, without forgetting the key actor, people.
Below are some of the characteristics that define a smart company.
A smart factory’s most crucial feature is its connected nature– the machines are embedded with smart sensors that continuously pull data from old and new sources. Thus, the data is constantly updated, representing the current situation. But the workers are also connected, with easy access to digitized standards and with tools to easily record any inconvenient or improvement idea. A Smart Factory is a paper-less factory.
Integrating the factory, business, and operation system provides a holistic view of the supply chain process. Further integration of smart machines with other parties such as suppliers and customer and again factory workers input provides greater overall supply network efficiency.
Smart machines allow the running of day-to-day operations with minimal human intervention. This optimization leads to high levels of reliability. So workers can focus on the important things like how to analyze that data into information for a quicker decision making. And when human intervention is needed, smart factories have it standardized and digitized.
The synchronization of machines and automated workflows improves the tracking and scheduling of events. This integration, in turn, optimizes the consumption of energy and other resources.
Hence, smart factories increase uptime, yield, and quality. Technology also helps in maximizing efficiency but cutting costs.
In smart factories, the data provided is transparent. Real-time data visualizations capture the data in the still-in-production products and transform them into actionable insights. Even more, throughout a digital continuous improvement system transparency is a given, every department is responsible of its data and the data provided to the overall company data hub.
Indeed, a transparent network enables greater visibility across production facilities. It also ensures that the organization makes accurate and timely decisions. Some tools that support transparency are real-time alerts, monitoring and tracking, and role-based views.
Digital connectivity enables employees to anticipate and act on issues before they occur. This proactive feature helps identify anomalies, identify and address quality issues, and monitor safety concerns. A proactive system also comes in handy in replenishing stock and predicting customer needs. A smart company can also predict future outcomes based on historical data. This ability helps the management create better forecasts and customer satisfaction.
Smart factories can also use the digital twin to digitize operations. Such technologies help the factories to move beyond integration into the predictive analysis.
The agile feature of industry 4.0 allows it to adapt to changes in schedule and product details with minimal interventions. Smart companies equipment and material flow in line with schedule and product changes. For instance, all the working instructions you had in the factory on paper, can now be replaced by video work instructions that can be improved on the fly and get a quicker approval.
The same applies when implementing improvement ideas, which can be easily managed in a smart factory through digitalization. This increases both the engagement of employees and the effectivness of the new improvements.
All these take effect in real-time, thus avoiding any build-ups. Also, agility improves production uptime and yield by minimizing the change-over effects. Agility is an essential smart factory feature, especially regarding the flexible scheduling of factory products.
When combined, these features allow manufacturers greater visibility across the factory. They also help managers navigate most of the challenges faced in traditional production, which leads to factory losses.
What technology is needed to upgrade to a smart factory in industry 4.0
In the fourth industrial revolution, smart factories used various technologies to optimize production processes. These technologies include but are not limited to the following:
Internet of things
One of the essential features of industry 4.0 is the internet of things. This technology refers to the interconnection of computing devices embedded in devices through the internet, forming a giant network of things and people sharing information.
In production, the floors and walls of factories are installed with sensors. These sensors have IP addresses connecting machines with web-enabled devices such as phones and computers. The network allows high-level data collection and analysis.
AI and machine learning
AI and machine learning allow the efficient use of the information gathered using the internet of things or in any software to support improvements in the plant. The technology also integrates the information collected from the factory floor with other business units. In extension, AI incorporates data from partners and other parties if they are part of the network. For instance a proposed date and team member for an action to be done based on similar actions collected and completion time. But again, people knowledge base also help AI to provide better resolutions not only in machines.
The AI technology then uses this information to forecast and predict the future movements of production. Another capability of AI technology is that it indicates the future operation ability of the factory floor network. For example, AI will indicate the failure of one machine, which, if not detected, could distort the data analyzed. AI also helps point out areas of wastage or where the machines are not in optimal production.
Cloud computing is the real-time or on-demand access to computing resources over the internet. The components of cloud computing are physical and virtual servers, data storage, networking capabilities, and remote development tools. These applications are hosted at a remote data center and managed by cloud service providers (CSP).
Cloud computing is an essential component of Industry 4.0, especially regarding factory support services. For instance, the purchasing, finance, and sales department can access real-time data and have remote interdepartmental meetings in case of emergencies.
Also, cloud computing saves on the technical costs of setting up a physical server. Cloud service providers host the data. Thus, the only cost that the organization incurs is the monthly subscription charges.
Edge computing is a distributed computing paradigm that brings data storage closer to where it is needed. Demand for real-time operations means that some data must be at the edge (consumption point).
Edge computing reduces the lapse of time from access of data to response. For example, the detection of failure of a conveyor belt requires real-time action as it could halt the whole production process.
The time taken to send the data from the factory cloud to the response team may be longer if there are network problems. If the factory machines had sensors that communicate such information directly, delays would not occur.
A digital twin is the virtual representation of a physical object that spans its life cycle. The thing could be an engine, building, or a car. It is updated on real-time data and uses simulation and machine learning to reason and help in decision making. Looking at the digital twin, you can get all the crucial information you need to understand how the physical object performs in the real world.
Digital twin helps developers to understand how products are performing in the present. This technology also predicts how the objects will perform in the future.
Digital twin helps the developers in achieving the below tasks.
Break down the boundaries that surround product innovation, creation, and testing.
Visualizing the products in use in real-time by real people.
Promoting traceability of the products in the market
Big data analytics
Big data analytics collects, records, stores, and analyzes high volumes of data. The technologies that support big data analysis include Hadoop, data mining, text mining, and predictive analysis.
Big data analytics aims to uncover meaningful insights such as hidden patterns and correlations. The technology also helps managers understand the information at their disposal.
Big data analytics provides new opportunities, alternatives to solving current risks, and business improvement channels. Moreover, using it helps the producers to make future decisions and optimize a company’s profitability.
3D printing technology
3D printing technology is also known as additive manufacturing. This technology involves creating a three-layered dimensional object using computer-created designs. The layers are added up to build the final three- dimensions image.
3D printing technology allows the users to create geometric parts with added depth. The cost of creating 3D designs is low, and the technology is also time-efficient. Because the technology uses Computer Aided Designs (CAD), product alteration is easy.
Because of its ability to create complex geometric parts, 3D printing technology is popular in the aerospace, medical, and automotive industries. Additive manufacturing also comes into play in project planning, particularly in visualizing the features of the final product.
mlean as a driver toward smart industry 4.0 factories
The core focus of lean manufacturing is improving efficiency by eliminating waste. Lean manufacturing integrates the 5Ms of manufacturing to create the best processes. These five Ms are manpower, machines, materials, methods, and measurements.
They are integrated into lean manufacturing as follows.
Manpower: You need employees to perform various duties and activities.
When employees are not satisfied, their output is also directly affected. Thus, employees should always be motivated to give the best result.
Machines ( equipment and technology)
Every manager should have an in-depth knowledge of the equipment they are operating. In addition, the workplaces should be safe, and every piece of equipment should be functioning well.
Lean manufacturing also supports continuous software improvement. The employees should therefore learn the software component to give the necessary feedback on areas of improvement.
Lean manufacturing adopts the just-in-time business model of stock management. This model helps to save on storage costs and stock opportunity costs. Thus, only the relevant materials should be available during production.
Lean manufacturing uses the standardization method to endure that the employees work as they should. For instance, the employees fill out standard forms in the area where they are performing. These forms have the relevant information regarding the duties, how to go about them, and the appropriate output.
It is essential to gauge the team member’s output. Lean manufacturing uses key performance indicators (KPI) to measure performance. The KPIs display schedules and targets of deliverables. They also indicate the results, measure them against actual goals and highlight the areas of improvement.
Below are some of the ways that lean manufacturing enhances industry 4.0.
Focus on quality
The aim of lean manufacturing is the elimination of waste. To achieve this, factories need faster and smoother supply chain management, from product manufacturing to delivery to the client.
When enterprises use smart industry technologies such as the Internet of Things (IoT), the managers get a full view of the production process and value chains. They can also detect machine malfunctions and prioritize urgent issues that would otherwise affect the factory uptime.
Focus on customer
Lean manufacturing emphasizes the need for feedback and customer satisfaction. The manufacturers can use AI technology to assess customer needs. For example, you can analyze customer behavior through the use of apps.
The customers are also able to customize their orders using the apps. Using bots also ensures that customers get instant feedback on and off working hours.
The digital twin also enables the manufacturers to assess the behavior of products in real-time. Thus, this technology helps the manufacturers to improve their output continuously.
Another objective of lean manufacturing is employee motivation through processes. Smart technologies come in through cloud computing.
In a smart factory business model, employees get the data as and when needed, improving efficiency. When the employees can easily achieve their goals, they are motivated to set other goals and excited to be part of the system.
Request a demo
Industry 4.0 is the new and smart way of doing things. The technology gives you a competitive end in modern-day manufacturing. The good thing is that achieving smart manufacturing is not difficult with the proper support. Contact us for a detailed discussion on how we can help.
To start positioning ourselves, and as we said in our 1st blog series about standardization, in phase C (Check) of the Deming PDCA cycle we had to do “The Job Observation”:
What is Job Observation
Ensuring the robustness of standardization is the main challenge. If you remember in the previous post we defined the best way to digitally standardize any activity. This is only the beginning, or rather it is the basis of our continuous improvement methodology since the ultimate goal of standardization is to make its accomplishment rigorous (whatever the stakeholder is), and at the same time be the basis of continuous improvement for any activity.
Job Observation is a tool that helps us achieve several goals. In this post, we will look at the different types of Job Observation methodologies, which will help us to:
Keep the standards “alive”
Ensure standards are followed and respected
Identify problems of any kind that affect the quality, productivity, ergonomics, safety, etc., of people or goods
Be able to identify opportunities for improvement of the standards
Identify training opportunities
Identify opportunities for “Kaizen” type improvement studies
How to do job observations effectively?
There are many ways to do job observations, but in order to make it effective, here are the main tools that we would like to propose:
The 3 types of observation by managers:
Observation for an unexpected event
What is “Genchi Genbutsu”
Genchi Genbutsu (“Go see yourself”) are Japanese words that are part of the TPS (Toyota Production System). This tool is especially recommended for managers, and it is based on the following concept: for any inefficiency, go to the source and see by yourself and with your own eyes,and if possible be also accompanied by your team. It is a basic principle for dealing with problems: go and observe the place or process where the problem has been detected. If this is clear to us, half of the problem is already solved. Managers must show the importance of working with “Facts and Data” and not with opinions or perceptions (whether they are interested or not) from third parties.
What are “Gemba Walks”
Gemba Walks, or maybe more known as plant tours, follow the same basic concept of Genchi Genbutsu, which has the same origin in the TPS. Gemba Walks are also very oriented to managers within companies with a strong Lean orientation. Gemba or “Place of great value”, is the place where things happen, and where we can perceive reality with the 5 senses and understand the current situation in the environment where they happen.
Gemba Walks should be done routinely, and the leaders of any organization should integrate them into their daily tasks. They get to know the day-to-day life of the place where the added value is generated and become familiar with the issues. The purpose of this practice is not to solve problems, make judgments, or give orders to change the results but to generate the spirit of detection and continuous improvement that will ultimately lead to solving the problems. This is critical.
We must also congratulate the teams when the results are positive. These “walks” will allow us to strengthen our relationship with our collaborators and to detect non-value-added tasks, trends to correct, patterns and problems that have not been analyzed, but also good practices and points of interest among other things.
Principles of job observation
1. Observing is working:
During the time spent observing, we are focused on it and therefore it is a time that we devote to observation, no other activity should distract us from observation, so forget about cell phones and WhatsApp. This activity, which is fundamental for all managers, should be a daily activity and should last at least 30 minutes a day.
2. Attitudes and behaviors of the managers during the observation:
Be unavailable for external calls
Prepare the documents
Remember the standards
Go to the workstation and inform the operator
Observe the operation from a distance several times
Closely observe the position
Dialogue with the operator
Make a balance and action plan
3. Observe with the 5 senses:
Taste (mainly for the food industry)
Hearing: noises, rustling…
Touch: vibrations, temperature…
Vision: leaks, dirt…
Smell: Smells of burning, chemical products…
4. Observation Filters:
We can make our observations in a general way in a job or we may want to establish a specific focus. When we focus, we are able to see many more opportunities for improvement. Here are some examples of approaches:
Compliance with standards
Production of defects
5. The 4 M’s:
The methodology we adopt must integrate the 4 M’s from the 5M Model (the M of Medium or Environment will be integrated into the rest of the M’s):
Compliance with standards
Work standard, or control
Means (machine, tooling):
6. Geographic perimeters:
The environment of the workstations or production lines:
Overview to appreciate weaknesses in the environment of the workstations, identification of aisles, forklift crossings, identification of fluids, emergency or evacuation exits, lighting, etc…
General view of a machine or process:
Overview of the machine or production line, how it is driven, maintained, repaired, how non-conformities are identified, etc…
Find the most relevant weak points of our machine that affect the results.
Particular focus on what is most relevant:
Where a defect occurs and why
Detail of the standards that affect our problem
The training of an operator
The 3 types of observation:
1. Planned observation:
This is the observation that is planned and part of a routine.
All Managers must perform their observations frequently. It is a fundamental routine in the daily management of any organization. Remember that observing is also working.
Observation by a Team Leader must be on a daily basis. The rest of the manager levels, will determine their frecuency, but it should be at least once a week and they should perfom it jointly with their lower levels.
2. Circumstantial observation:
This is the observation which comes as the consequence of a specific event, which can be:
The break of a medium or tool
A quality defect identification
3. Reflex observation:
It is the “Ideal” situation: all the personnel while in the Gemba, is observing in a natural way and is able to visualize any anomalous state. The 4 M’s are integrated in their 5 senses and while walking through any point of the factory, they are able to visualize anomalies or aspects to improve.
Observing is a management tool, and thus, it must be routinely trained.
How to digitally manage the Observation?
It has been proven that carrying out an observation routine is cumbersome. It generates a multitude of papers, Excel sheets, checklists, etc… that must then be transferred to the computer… (which becomes “a pain”). The management must afterward extract the conclusions of the observations, a multitude of actions, and people in charge, with very difficult management and control of all of them. In our opinion, the solution lies in a set of applications that digitally enable all of the above effortlessly and are capable of being tracked at the required level.
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