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Manufacturing industrial means of mechanization and automation of managerial and engineering work

Manufacturing industrial means of mechanization and automation of managerial and engineering work

But what if there's a way to rethink the concept of "work" that not only makes humans essential, but allows them to take fuller advantage of their uniquely human abilities? Will pessimistic predictions of the rise of the robots come true? Will humans be made redundant by artificial intelligence AI and robots, unable to find work and left to face a future defined by an absence of jobs? Or will the optimists be right? Will historical norms reassert themselves and technology create more jobs than it destroys, resulting in new occupations that require new skills and knowledge and new ways of working? The debate will undoubtedly continue for some time.

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Industrial automation enabled by robotics, machine intelligence and 5G

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The four evolutionary stages of manufacturing have brought us to Pharma 4. The first stage comprised the implementation of steam power to mechanization. The second involved mass production, and the introduction of the assembly line, powered by electricity. The third stage added computers and automation into the mix, and the fourth is the introduction of cyber-physical systems that enable the computerization of manufacturing Figure 1. This fourth stage, which is currently evolving before our own eyes, is the one that is becoming commonly referred to as Industry 4.

It would even seem that Industry 4. The new buzzword for this that appears to be gaining some traction is Pharma 4. Figure 1. The four stages of manufacturing. It represents the fourth industrial revolution on the way to an internet of things, data, and services. Decentralized intelligence helps to create intelligent object networking and independent process management, with the interaction of the real and virtual worlds representing a crucial new aspect of the manufacturing and production process.

The basic principle is that by connecting machines and systems, we can create intelligent networks along the value chain that control each other.

For example, machines would be able to predict failures and trigger maintenance processes autonomously, or self-organize logistics that react to changes in production.

Industry 4. In the past decade, these technologies have swept across the globe, as manufacturers across the world recognize the value of Industry 4. A vision of the future with efficient, self-automated manufacturing processes that monitor themselves, so they never go wrong.

Pharma 4. The Diagnosis Before the Prescription There are few people that would fault the vision, but a problem is emerging in the way that the principles of this industrial revolution are being implemented.

The potential for Pharma 4. If these two questions are not answered before embarking on the path to Pharma 4. The key technologies required for digital transformation cause radical changes in the business processes of any company, and those changes need to be discussed and understood before they are undertaken.

This involves overcoming a general reluctance to change that is typical of the human makeup, as well as training employees to ensure they are qualified to use the upgraded plant. Modern information and communication technologies like cyber-physical systems, big data analytics, and cloud computing, will help early detection of defects and production failures, enabling their prevention and increasing productivity, quality, and agility benefits that have significant competitive value.

This creates its own problems, both in terms of external data security and internal validation of the data. If a validated database is duplicated, does it need to be re-validated? These additional drains on IT and other resourcing need to be considered and discussed—sometimes an alternative approach is available that avoids these issues, but still allows the company to move forward with digitization.

New technology needs to be reliable and stable for critical M2M, and it needs to meet any applicable regulations to the industry sector concerned.

Of course, the economic benefits of this considerable investment need to be justified, and an expected return on investment ROI for each stage should be estimated. Investments need to be prioritized to ensure that those providing the greatest ROI are implemented first, and all changes need to be based on strategic plans to place the company at an advantage, or at the very least maintain a current favorable market position, in the future. Continuous Process Verification Pharmaceuticals represent one of the most regulated industries, and thus, provide a good opportunity to demonstrate an optimal approach for digitization.

Pharmaceutical companies often adopt Continuous Process Verification CPV , through which all data generated during product manufacturing can be continuously assessed and validated against regulatory guidelines, to ensure they stay within the parameters documented when those processes were validated. Hundreds—sometimes thousands—of variables must be monitored to verify that they remain within the specifications established for this process.

This is an ideal application for Industry 4. Figure 2. Sometimes pharmaceutical companies find challenges related to consistent product quality. Data analytics technology can often be utilized to address such issues to improve the quality of their product, manufacturing processes, and profitability. Analytics is Key One pharmaceutical company was having problems with sub-standard raw materials that were not being detected until a batch of product had been completed.

Data analytics technology was used to provide a single dashboard view of the process, from incoming raw materials to outgoing product Figure 2. The dashboard clearly showed critical parameters with real-time reporting of any issues likely to affect the product under manufacture. Underlying the success of this project, a clear goal had been set, addressed, and completed, setting the company on its path to Industry 4.

Other benefits of digitization include the continual assurance of process control, and the ability of data analytics to quickly detect any deviations from expected parameter limits. This automatic monitoring and control enable pharmaceutical companies to offer continuous data that are validated against regulatory guidelines, helping them to comply with the rigorous requirements associated with their industry sector.

The technology also automatically generates annual reports, or reports required for site inspections by regulatory authorities, potentially saving hundreds of man-hours every year. The Path to a Digital Transformation Our world is becoming increasingly digitized, and this can be a good thing—improved efficiency, enhanced quality, and better company compliance with ever-increasing, data-related regulatory requirements.

However, before embarking on the journey to Industry 4. There is no shortage of technologies, but choosing the one that is going to have the greatest positive impact on your company, in the area that you most need it, is an obvious crucial decision.

Determining how to approach your technology choices can be resolved by creating a step-by-step process with specific milestones for each activity. This should be a team effort with relevant constituent participation.

The first step is to identify the problems you hope to solve and what challenges are in the way. Second, identify the team. Who has the technical expertise to identify the parameters of importance? How is the IT going to help access key data sources? Then take a look at the people and technologies involved. What talent and technologies are needed? For example, if looking to maximize existing technologies and data sources, what platforms are compatible with current equipment and will be scalable going forward?

All of these steps can help avoid potential problems and set your company on its path to Pharma 4. Connect with Pharmaceutical Processing on Social Media.

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Automation, robotics, algorithms and artificial intelligence AI in recent times have shown they can do equal or sometimes even better work than humans who are dermatologists , insurance claims adjusters , lawyers , seismic testers in oil fields , sports journalists and financial reporters , crew members on guided-missile destroyers , hiring managers , psychological testers , retail salespeople , and border patrol agents. Moreover, there is growing anxiety that technology developments on the near horizon will crush the jobs of the millions who drive cars and trucks, analyze medical tests and data , perform middle management chores , dispense medicine , trade stocks and evaluate markets , fight on battlefields , perform government functions , and even replace those who program software — that is, the creators of algorithms. People will create the jobs of the future, not simply train for them, and technology is already central.

Automation has the potential to transform future jobs and the structure of the labor force. As we discussed in the March edition of the QEB , automation in manufacturing has steadily decreased costs for decades, making US manufactures more competitive while also reducing the amount of labor required to produce them. Looking forward, technical advances in computing power, artificial intelligence, and robotics have created the potential for automation to penetrate deeply into occupations beyond manufacturing. The prospect that future automation might transform jobs and the labor force on a systemic scale raises some important questions for workers compensation:. Because of the breadth of this topic, we will present our analysis in two parts.

Pharma 4.0: Industry 4.0 Applied to Pharmaceutical Manufacturing

Our mission is to help leaders in multiple sectors develop a deeper understanding of the global economy. Our flagship business publication has been defining and informing the senior-management agenda since As automation technologies such as machine learning and robotics play an increasingly great role in everyday life, their potential effect on the workplace has, unsurprisingly, become a major focus of research and public concern. In fact, as our research has begun to show, the story is more nuanced.

Mechanization

NCBI Bookshelf. In , Delmar S. It had been increasingly applied across the US, Europe and Britain throughout the inter-war period in a range of manufacturing contexts, including the production of textiles, cigarettes, the chemical industry and other processes where very large outputs were required. However, in the post-war period, the issue of automation and its impact, not only on the lives of individual industrial workers, but also on the psychosocial foundations of the nation as a whole, became a subject of widespread debate.

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The Fourth Industrial Revolution will see the convergence of artificial intelligence and data technology as a new solution to address industrial and social problems across the globe, by integrating cyber and physical fields.

In the era of Industry 4. Leveraging automation and advanced technologies, like robotics and ERP solutions, are enabling even greater gains in productivity to be made each day. These are not easy components to juggle all at once. To talk about automation and modern manufacturing. Industry 1. Also known as the first industrial revolution, Industry 1. Industry 2. The second Industrial revolution saw the arrival of Aviation, Radio, and Assembly-line manufacturing, with electricity powering it all. Industry 3. This was due largely to the invention and adoption of such technologies as computers, the internet, and Information Technology.

Robotics is a field of engineering that deal with design and application of robots and the use of computer for their manipulation and processing. Robots are used in industries for speeding up the manufacturing process. They are also used in the field of nuclear science, sea-exploration, servicing of transmission electric signals, designing of bio-medical equipments etc. Robotics requires the application of computer integrated manufacturing, mechanical engineering, electrical engineering, biological mechanics, software engineering.

In order to retain a certain level of production in Norway, suppliers to the Norwegian maritime industry need to lower their production costs. Automation is generally an effective way of achieving this in standardized high-volume, low variety production.

Industrial automation is the use of control systems, such as computers or robots, and information technologies for handling different processes and machineries in an industry to replace a human being. It is the second step beyond mechanization in the scope of industrialization. Earlier the purpose of automation was to increase productivity since automated systems can work 24 hours a day , and to reduce the cost associated with human operators i. However, today, the focus of automation has shifted to increasing quality and flexibility in a manufacturing process. In the automobile industry, the installation of pistons into the engine used to be performed manually with an error rate of Presently, this task is performed using automated machinery with an error rate of 0. Lower operating cost: Industrial automation eliminates healthcare costs and paid leave and holidays associated with a human operator. Further, industrial automation does not require other employee benefits such as bonuses, pension coverage etc. Above all, although it is associated with a high initial cost it saves the monthly wages of the workers which leads to substantial cost savings for the company. The maintenance cost associated with machinery used for industrial automation is less because it does not often fail.

Automation, now going beyond routine manufacturing activities, has the potential, as McKinsey's Michael Chui explains how automation is transforming work. of efficient, technology-driven stock management and logistics, for example. be automated doesn't mean that it will be—broader economic factors are at lyceum8.comg: mechanization ‎| Must include: mechanization.

Manufacturing engineering

We use cookies to improve your experience on our website. By using our website you consent to all cookies in accordance with our updated Cookie Notice. Nearly half of the tasks currently undertaken by humans could already be automated , even at current levels of technology. Within the next decade it is likely large sections of society will be looking for new jobs. The first industrial revolution used steam power to mechanise production.

The Fourth Industrial Revolution and Precision Agriculture

The four evolutionary stages of manufacturing have brought us to Pharma 4. The first stage comprised the implementation of steam power to mechanization. The second involved mass production, and the introduction of the assembly line, powered by electricity. The third stage added computers and automation into the mix, and the fourth is the introduction of cyber-physical systems that enable the computerization of manufacturing Figure 1. This fourth stage, which is currently evolving before our own eyes, is the one that is becoming commonly referred to as Industry 4. It would even seem that Industry 4. The new buzzword for this that appears to be gaining some traction is Pharma 4. Figure 1. The four stages of manufacturing. It represents the fourth industrial revolution on the way to an internet of things, data, and services.

At Productivity, we know that change can often be overwhelming and frightening. Our experts are here to prove that there are a multitude of benefits when you upgrade to automation.

Automation , the application of machines to tasks once performed by human beings or, increasingly, to tasks that would otherwise be impossible. Although the term mechanization is often used to refer to the simple replacement of human labour by machines, automation generally implies the integration of machines into a self-governing system.

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Manufacturing Engineering it is a branch of professional engineering that shares many common concepts and ideas with other fields of engineering such as mechanical, chemical, electrical, and industrial engineering. Manufacturing engineering requires the ability to plan the practices of manufacturing; to research and to develop tools, processes, machines and equipment; and to integrate the facilities and systems for producing quality products with the optimum expenditure of capital. Manufacturing Engineering is based on core industrial engineering and mechanical engineering skills, adding important elements from mechatronics, commerce, economics and business management.

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