What is the Role of Retrofit Engineering in Product Development?

November 24, 2020

The product development process is a series of interdependent and routinely overlapping tasks that convert an idea into a prototype building and on to a marketable product. Companies ensure that processes are smooth and flexible for the consumers. As the original idea advances through the development process, it is refined and routinely evaluated for commercial and technical feasibility. Trade-offs between the various objectives such as price, market availability, cost, market availability, performance, quality, and reliability are made throughout the process. Now, there is great hype about designing for manufacturability. The focus is on the businesses’ internal manufacturing systems. Yet, when those accountable for design ignore the manufacturing process and technological capabilities of outside suppliers and enterprises, problems with control, time-to-market, quality, configuration, and cost are inevitable. If optimal design performance is to be achieved, manufacturers must be active from the start, when they can have a significant impact on cost, time, performance, and quality. Selected suppliers should participate in value engineering, prototype failure, feasibility studies, and stress analysis, among other product development tasks.

Retrofit Engineering in Product Development

Extensive rework, redesign, and retrofit operations are normal when a company is working in the conventional functional model. Ultimately, the absence of teamwork results in processes that are a continuing problem on the firm’s long-term competitiveness. The design and development of new products are one of the manufacturing firm’s most essential tasks as it affects profitability and even survival. The firm’s suppliers and supply management have key contributions to make during this process. A growing number of successful manufacturing firms involve supply management and suppliers upfront because of contributions they can make in the areas of cost, quality, and time to market.

The global competition and global marketplace, combined with modern computers, communication systems, and sophisticated software, have developed an environment where “time to market” and first to market have tremendous competitive advantages. Significantly, the need to decrease development time has forced enterprises to look for new methods to compete. The use of suppliers and supply professionals earlier in the product development cycle is a crucial way to decrease time to market. The benefits of an integrated approach to new product development no longer can be ignored. The lack of effective, cooperative teamwork among the functions just noted routinely has been accompanied by cost overruns, quality problems, major scheduling problems, forgone all-in-cost savings, and new products that are late to enter the marketplace. Also, early recognition of difficulties is impossible or difficult in the absence of cooperative teamwork.

As the machinery and products of the companies, organizations, and people in general ages and becomes less effective with time, the services of the product and machinery become a crucial part of the operations. Routine services not only avoid breakdowns but also enhance the product’s productivity and reliability. Almost all of the successful companies focus on their core competencies to drive profits and hence require regular servicing of their machinery to keep up with the technological advancements. Even a small breakdown in the machinery and products can halt most of the organization’s operations resulting in a significant number of problems. Retrofitting is one of the most important ways that can enhance the performance of aging machines and products.

Retrofit engineering is an incredible way to minimize the risk of machine breakage and unplanned machine shutdowns in an organization. It helps in servicing aging equipment and outmoded machinery. It may involve enhancing the reliability and maintainability of the system and subsystem. It is also useful in redesigning mechanical, electrical, and software systems, subsystems, and various other components. Retrofit engineering is helpful in replacing outdated technology with innovative and modern solutions. It increases the mean time between product failures and helps in the development of in-house diagnostic and maintenance capabilities. Various steps of a typical retrofit engineering project are:

  • Analyzing the exiting design and reviewing the documentation
  • Creating the new design or re-engineering the existing design
  • Simulating to verify functionality
  • Assembling prototype to verify design
  • Validating through testing and demonstration of the prototype
  • Generating complete technical data package to support design

Retrofitting is the process of replacing obsolete operating systems and machine components to extend the working life. It benefits the organizations as retrofitting incurs lower costs as compared to purchasing the new machine. It enhances the precision of the machine and delivers quality output. It is essential for an organization to maintain the machine at an optimum quality hence required to be retrofitted routinely to increase the economic efficiency and productive operation. Most of the developing and underdeveloped countries depend on retrofitting as they have lack of adequate foreign exchange resources for machinery import.

Retrofitting is a smart investment and is essential for competitive businesses. The up- gradation of the machinery as per the latest technological advancement is essential for the efficiency of the organization. The rate of investment in retrofitting is immense as it delivers on performance and keeps the business moving. It can be applied for reducing the machinery setup, minimizing the downtime, increasing processing speeds, minimizing minor stoppages, and enhancing production part yields.

Reducing the machinery setup is an important thing to enhance the productivity and effectiveness of the operations. It typically involves data entry steps, selecting fixtures and materials, loading new tools into the machine, etc. Automating most of the machine setup enhances productivity as compared to traditional methods of involving various steps to external and parallel processing to the machining process. The traditional are prone to risks and errors and exceeds the processing time. Automation allows easier management of multiple machines rather than focusing on multiple setups.

Manufacturers are increasingly utilizing machine tool probes by retrofitting machine tools as they are fast and robust. They are smart and can automatically set tool wear, workpiece offsets, and tool geometry. Though manufacturers are often worried about the machine tool probe cycles. They are faster and more accurate than an operator could be. They are consistent and eliminate operator measurement and data entry time variation. They eliminate errors and can work through lunches and breaks. Retrofitting engineering can also be applied to the machines or their components for reducing the downtime. This can be done through maintenance training, backup and restoring, remote diagnostics, and performing crash protection. Machine crashes due to setup errors enhance the downtime hence it is important to automate and error-proof most of the processes.

Product development through retrofit engineering is diverse and filled with complexity. The management and engineering of retrofit projects should have an experienced team of staff with optimum skills and motivation. Sometimes, the effort required to retrofit an existing product is greater than the development of new products. Also, products developed through retrofitting are also exposed to a diverse set of risks and require active management. The reason for the retrofit products is to manufacture higher-value products and to enhance plant efficiency. This generally leads to infrastructure modernization increases the production capacity beyond present capability.

An engineer should have detailed knowledge of design and operating procedures for an existing product and should select engineering standards and specifications for compatibility with an existing product. The successful management of retrofit engineering requires a clear set of objectives along with a specific implementation strategy. It requires effective planning and progress monitoring.

The initial development for retrofit products requires the identification of necessary objectives. It is followed by feasibility studies and the selection of preferred solutions for retrofitting. Next, it is recommended to refer to the existing data and design of the products as it helps in deciding the measures to be taken while working on the product. It is essential to study the existing drawings and guidelines of the product to ensure compatibility for retrofitting. It is essential to detail the process elements and flow schemes clearly as per the design requirements. Having a retrofit strategy is crucial for the enhancement of the product functions. It is necessary to have a safe approach while handling the product and should handle specific time-sensitive elements.

The most important aspect of the implementation of retrofit engineering in the advancement of existing products is the quality, availability, and motivation of the engineers working on product development. They should possess specific skills and knowledge as it can ensure the project to be completed in a timely manner. The composition of the core team for the retrofitting of the product should be adept with specific know-how of the product. It is important for the individuals at the core team to be available when needed and should possess specialist skills. The project manager should possess essential leadership skills and ensure that the staff is motivated.

Also Read: How Rapid Prototyping Helps You Design And Develop Products Quickly

Value Analysis and Value Engineering in Production and Operations Management

November 18, 2020

With the advent of enhancement in technology and increased competition among the businesses, there is a growing need to reduce the product price. It puts pressure on the businesses to lower their manufacturing and production costs in order to sustain in a highly competitive world. Product engineers are continuously challenged with the need for a reduction in production and material costs. Various management techniques are applied to enhance the profit by specifically targeting the production and manufacturing costs. Materials and overheads represent a large chunk of the total costs and managers work upon strategies to control them. The costs are regulated not only by the efficiency of the execution of the methods but also by the strategies involved in the design, detailing, marketing, research, and development.

Value Analysis and Value Engineering in Production and Operations Management

Businesses are evolving their product’s designs to minimize the product cost as products incurring greater costs become obsolete faster. This requires the transmission and estimation of correct costs during the design process. It is a complete teamwork and communications are necessary for the regulation of work costs. Value analysis and value engineering services are two such processes that drive down the production costs and help businesses to remain sustainable.

Value analysis is a process of a systematic review and is applied to the designs of existing products. It is helpful in delivering the products at a lower cost with specific performance and reliability. It is concerned with the functionality of a product as per the customer’s demand. This process meets the specification and performance criteria of the customer. Basically, there are three principle costs of products namely, cost of parts, direct labor costs, and overhead costs. But now businesses are also focusing on costs related to manufacturing, assembling, poor quality, and warranty.

Value engineering acknowledges the economic, psychological, and social cues that may decrease the value of a product or service and rarely implies the working aspects like neglect of responsibility. Poor Product value can arise due to the following reasons.

  • A negative attitude toward the product or service, Failure to fulfill the required innovativeness and creativity.
  • Failure to accept or seek advice in need and unwillingness to admit a lack of knowledge or education on certain aspects of project development.
  • A proclivity to emotion-based decisions rather than fact-based decisions.
  • Rigid application of SOPs without adapting to change in technology and design.
  • Insensitivity to customer or client needs.
  • Lack of good communication and poorer human-to-human relations.

The principal focus of the value analysis process has been the administration of functionality to offer value to the customer. Businesses reduce the production costs of the product by eliminating costs that have no functional value to the client without negatively affecting the quality, maintainability, functionality, and reliability of the product. The goal of the value analysis approach is to create value for money by being inexpensive. This can be done by identifying activities that reduce the maintainability of the product as that enhances the cost of ownership and lowers the value attached to the product. But it doesn’t mean removing activities that compromise the reliability and quality of the product because it lowers customer value, enhances customer complaints while lowering product sales.

Value analysis is utilized for a complex number of reasons to reduce the costs. There are numerous design-related issues for the application of value analysis in a product within the business. Some of these are related to technology replacement, mediocre practices, traditional thinking, and inadequate analysis. Other internal reasons for conducting a value analysis approach in a product include the products with unknown problems, unending/varying customer demands, corrective actions, enhancement in product margin, and safety and compliance requirements. Many times, the market determines the cost of the product and any attempt to lower the costs through enhancement activities can deliver a greater return on investment throughout the product life cycle. The value analysis approach is also applied due to the various market induced reasons. These reasons relate to pricing practice, new technology and materials, environmental issues, e-commerce growth, compliance, and quality regulations.

Most businesses apply value analysis to the existing products that are sold in large numbers. The existing products tend to offer a large amount of information for the improvement of the product. The performance of a product can be analyzed by different managers who can present their opinions and complaints regarding the products. The opinions of the managers are very necessary as it benefits the management to analyze the activities that attract costs from raw materials to final products. These discussions facilitate learning and allow managers to understand the boundaries of product redesign and re-engineering activities. Some of the limitations that the product management team come across before the re- engineering activities are related to the inability of businesses to change existing product design as it may incur tooling expense. Sometimes management has very little time to complete the project and make only minimal changes in the product design. Also, the greater levels of purchased costs in the supply line need an active engagement with the suppliers from the management which may consume greater resources and time.

Value engineering is a similar approach to value analysis but is applied to new products. It is applicable to an uncertain environment and has very little information available with the managers to make the decisions. It is a systematic process for the review of existing products. It requires a greater amount of investment in terms of skilled human resources. The results of the value analysis are similar most of the time and have certain commonalities at different stages of production. When the project team finds the commonalities with many products in the production line, it utilizes the horizontal deployment of the value analysis to make all the changes quickly and efficiently on a factory-wide basis.

The value analysis in a product can be a huge success for a business if applied in the right way. The early step of organizing an adept team for the project along with retrieving sufficient information for a product is essential for the success of the project. Businesses initiate the activities of the value analysis by gaining approval from senior management. The support and endorsement of top management are crucial for the legitimacy of the project. A single senior manager is enlisted with the management of the project with a single authority. This is followed by the selection of an operational leader to coordinate the various activities of the project. The management creates a reporting procedure for monitoring and controlling the achievements of the project against time. Regular communication among the members of the team is necessary to achieve the wider objectives of the project successfully.

People working with value engineering need continuous training to implement its chief modern technology to utilize step by step in an organized problem process. The guidelines should be systematically followed in order to focus on significant details. They must develop the skill to apply the scientific method with accurate data in order to challenge their problem- solving skills in real-time. The use of cheap material should not be made the criteria to manufacture the product as it may involve the costly process of manufacture and will cancel the profit. Regular workshops and training should be provided to employees as it offers them to fill the gaps in the information to make key decisions in product development.

Value engineering in the modern era needs to generate regular comparable data so the solutions are routinely accessible and readily used. It facilitates to bring better decision making and enhances the quality of the product in the long term. Organizations are now focusing on enhancing their daily work via this technique to improve their tasks. This brings more creative participation to the team and the responsibility is shared by the whole organization.

Many research study shows that a lack of management support is the principal cause of the lack of use of value engineering in businesses. The senior management should appreciate the benefits of value engineering in product design and development to ensure improving the functionality and decreasing the costs. Many industries are recognizing this technique as an effective management tool and agree that various problems that exist in their sector can be orderly removed with value engineering. The next phase of this technique will require the amalgamation of data with new technologies like artificial intelligence and virtual reality that can increase productivity by significant numbers.

Also Read: Reducing The Cost Of On-Road And Off-Road Vehicle Via Value Engineering

Role of Computational Fluid Dynamics in Product Manufacturing

November 10, 2020

Computational fluid dynamics or CFD involves the analysis of fluid flow, heat transfer, and associated systems with the help of computer-based simulation. It has a wide range of industrial and non-industrial applications and is a very robust tool for product manufacturing. It is excessively used in automobile industries for predicting drag forces and lift of the vehicle. Computational fluid dynamics requires significant knowledge in fluid dynamics, mathematics, and programming. It involves assuming the wide-ranging of variables to generate models that can capture the required needs for the actual real-world system.

Role of Computational Fluid Dynamics in Product Manufacturing

Computational fluid dynamics technique is utilized for the study of aircraft and vehicle. It is helpful in analyzing the lift and drag of the vehicle. The hydrodynamics of ships can be easily examined with this method. The study of combustion in internal combustion engines and gas turbines in industrial power plants and the flow inside rotating passages and diffusers in turbomachinery can be easily done with the use of this technique. In biomedical engineering, it is employed for blood flow analysis through veins and arteries. It is also used for weather prediction by the meteorology department. Modern environmentalists are also using this technique for determining the distribution of effluents and pollutants.

Industrial units are in awe with the computational fluid dynamics as it offers unique advantages over the experiment based techniques to fluid or flow systems design. It allows unlimited levels of details of results and helps to perfect the fluid systems. It reduces the lead times and costs of new designs for a system substantially. CFD facilitates analysis of the system where controlled systems are difficult to perform. It also has the ability to examine systems under disastrous conditions at and beyond their normal performance units. In experimentation studies, the costs of hiring personal and other aspects are variable and hence experimentation is increasingly being ignored by the industries. On the other hand, computational fluid dynamics deliver a huge volume of results without any added cost and is very cheap to perform.

Fluid flow problems can be tackled by computational fluid dynamics codes. These codes are structured around the numerical algorithms and allow smooth access to solve difficult fluid flow problems. A computational fluid dynamic codes consist of a pre-processor, a solver, a post-processor.

The input of a fluid problem to a CFD program for transformation into an easy part comes into the context of pre-processing. It basically involves defining the geometry of a particular region, ie. a computational domain. It is further divided into a number of smaller, non- overlapping sub-domains in the form of mesh or grid of cells that helps in grid generation. It helps in defining and modeling of fluid properties of a fluid. The solution to such variables such as temperature, pressure, etc. is defined at nodes at each grid. The accuracy of any CFD solution is governed by the number of cells in the grid as the greater the number of cells or grids, the greater the solution accuracy. The fineness of the grid depends on the cost of the system and the accuracy of a solution. Most of the time of any computational fluid dynamics project is utilized at grid generation and domain geometry.

The finite difference, finite element, and spectral methods are three basic numerical solution techniques out of which the finite difference method is mostly used. A numerical algorithm involves integrating the basic equations of fluid flow over all the finite volumes of the region. The resulting integral equations are then transformed into a system of algebraic equations. The algebraic equations are then solved by an iterative method. The basic difference between the finite volume method and other CFD techniques is the integration of the control volume in the finite volume method. The resulting equations have the same properties for each finite-size cell. This simple concept makes it easy for engineers to understand the fluid flow as compared to other methods. The conservation of various flow variables such as enthalpy, velocity within a finite control volume is expressed to estimate whether it increases or decreases. Computational fluid dynamics codes consist of discretization techniques that are helpful for convection, diffusion, and other key transport phenomena.

The ever increasing popularity of CFD software has extended the processing capabilities. It has facilitated great graphic capabilities along with domain geometry, and grid display. The software package of CFD now includes vector plots, line and shaded contour plots, contour postscript output, and particle tracking. These facilities are enhanced by the animated and dynamic result display. This has allowed transmission of ideas to people of non-engineering backgrounds.

The fluid flow problems are built on complex sets of physics, chemistry, mathematics concepts, and mastering them requires skillful professionals. The user must possess significant knowledge in the various subjects prior to the simulation of CFD problems. The user must be able to identify and formulate the chemical and physical aspects of the flow problem. The key decisions that go with the modeling of fluid flow are the effects of ambient temperature, variations in air density, turbulent flow, and air bubbles, etc. The right decisions should be made while modeling the equations as to preserve the necessary characteristics of the problem. The accuracy at the simplification of the equation allows the greater quality of the CFD. The detailed description of the domain geometry and grid design is crucial at the initial stage for obtaining successful simulation results. Successful simulations can be obtained by convergence and grid dependence. A converged solution can be achieved by selecting various acceleration devices and relaxation factors.

The converged solutions are filled with varied issues and require optimization. The optimization of the solution with speed needs extensive experience at the evaluation of the code. The initial grid design depends on the characteristics of the flow. It is filled with numerous errors and requires refinement. Errors can be eliminated by performing a grid dependence study. Each algorithm has a unique error pattern and can be guessed by an experienced professional who has a thorough knowledge of the algorithm.

Computational Fluid Dynamics (CFD) is a way of reorganizing such processes and systems in a series of differential equations by using digital computers. It offers qualitative and quantitative reasoning of fluid flows by the use of mathematical modeling, discretization, and other pre- and post-processing tools. It has helped the scientists enormously in the development of fluid dynamics. It has replaced the traditional approaches to fluid dynamics with more powerful computational tools. The results of the computational fluid dynamics are equivalent to the actual laboratory results.

The ultimate goal of growth in the CFD field is to offer a capability comparable with other CAE applications such as stress analysis codes. The key reason why CFD has remained behind is the significant complexity of the existing behavior, which precludes a description of fluid flows that are simultaneously economical and complete.

The availability of affordable high-performance computing hardware and the introduction of user-friendly interfaces have led to a recent upsurge of interest, and CFD has entered into the wider industrial community. The variable expense of an experiment, in terms of facility hire and/or person-hour costs, is directly proportional to the number of data points and configurations tested. Whereas CFD codes can generate extremely large volumes of solutions at no added expense. It is very cheap and easy to perform parametric studies such as optimizing equipment performance.

The accuracy of a Computational fluid dynamics solution is determined by the number of cells in the grid. Generally, larger the number of cells, the better the solution accuracy. Both the accuracy of a solution and its cost in terms of necessary computer hardware and calculation time is dependent on the fineness of the grid. Optimal meshes are often varied, finer in places where greater variations occur from point to point and coarser in regions with relatively less difference.

Efforts are underway to generate CFD codes with a self-adaptive meshing ability. Ultimately such programs will itself refine the grid in regions of rapid variations. A significant amount of basic development work still needs to be done before these programs are robust enough to be incorporated into industrial CFD codes. The main ingredients for success in CFD are experience and a thorough understanding of the physics of fluid flows and the fundamentals of the numerical algorithms. Without these, it is very unlikely that the user will get the best out of code. It is the intention of this book to provide all the necessary background material for a good understanding of the internal workings of a CFD code and its successful operation.

Also Read: Applications Of Computational Fluid Dynamics

Design Principles and Best Practices for IoT Applications

November 4, 2020

Internet of things or IoT is a splendid collection of intercommunicating smart devices and solutions. These devices and solutions are driving modern technology and is an important aspect of the 21st century. It is a network of uniquely identifiable devices or things that are connected to the internet. These devices or things are programmable and have sensors to interact with humans or each other. IoT has been serving consumers with home automation, consumer electronics, industrial automation, etc. The key enabler of all IoT devices is the network as it integrates with a wide array of communication technologies. IoT applications are utilized in transportation, environment, energy, assisted living, smart cities, etc.

Design Principles and Best Practices for IoT Applications

As the digitalized world is getting increasingly interconnected with social platforms and artificial intelligence, the internet of things is the next big thing that is impacting each sector of the industry. Through IoT, machines are able to make decisions autonomously and industries are increasingly relying on automated machines for productivity without much human intervention. From smart thermostats that can adjust the home temperature to refrigerators that can automatically order food is low, IoT has been evolving with solutions that are benefiting the consumers immensely.

IoT services are attached to sensors and are connected to the internet. The IoT technological advancements and convergence within the IoT related technologies shape dynamically the development of new business models and IoT ecosystems. These ecosystems comprise of stakeholders representing the IoT application value-chain: components, embedded processing and communication, chips, service provision, architecture design, sensors, actuators, system integration, middleware, software, security, usage, test, etc.

This new model facilitates integrating the future generations of applications, network technologies, embedded systems, devices, and other evolving ICT advances, based on protocols, open platforms and standardized identifiers, and architectures. The deployment of IoT Large Scale Pilots (LSPs) to promote the market improvement of IoT and overcome the segmentation of vertically oriented architectures, closed systems, and application areas is the next important step in IoT development. Large Scale Pilots can address the concerns in different application areas by bringing together the technology supply and the application demand sides in real-life settings to demonstrate and validate the IoT technology in the real world.

While human social and economic activities continue to gravitate towards urban centers, Smart Cities deploy digital and telecommunication technologies to increase administration efficiency and improve the quality of life of their inhabitants. Cross-domain challenges in public safety, mobility, lighting, and energy efficiency can be addressed by user-centric ecosystems of interoperable vertical sub-systems. The integration and compatibility of sensors and actuators of connected sub-systems that are often complementary in the public space, in turn, stimulate the development of novel data-driven value-added application domain services. Due to their high density and ubiquitous nature, connected systems offer the prospect of evolving into platforms acquiring domain-level contextual information and delivering application management functions to diverse domains’ stakeholders. The LSPs need to address challenges in the fields of standardization, cyber-security, open data governance, and privacy and validate the novel business models underlying the services provisioned by future domain infrastructures. These IoT LSPs have to address technology challenges across the industrial sector verticals and go beyond the M2M, IoT vertical applications developed in recent years, in order to break the silos and to evaluate the real impact of IoT technology across industrial domains. The definition of themes needs to have a broader perspective and go beyond the narrower use cases proposed until now since in the future that cross-vertical collaboration and integration will be among the primary benefits of IoT.

Healthcare and wellness provide unique opportunities for extensive IoT implementation. Health care treatments, cost, and availability cater to society and the citizens striving for longer, healthier lives. IoT is an enabler to achieve enhanced care for patients and providers. It could generate greater asset utilization, new revenues, and reduced costs. In addition, it has the capability to change how health care is delivered. The development of the Internet of Health (IoH) applications dedicated to citizens’ health and wellness that spans care, medication administration, diagnostics, monitoring, fitness, etc. will allow the citizens to be more involved with their healthcare. The end-users could track the vitals signals with wearable devices, access medical records, get diagnostic lab tests conducted at home or at the office building, and monitor the health-related activities with Web-based applications on smartphones. The application of IoT in healthcare can enhance the access of care to people in remote locations or to those who are incapacitated to make routine visits to the hospital. It can also enable a quick diagnosis of medical conditions by monitoring and analyzing a person’s parameters. The medical treatment administered to the person under care can be enhanced by studying the consequence of therapy and the medication on the patients’ body.

The IoT applications in the buildings are interacting with the smart Building Management Systems (BMS) with an IP network, connecting all the building services while analyzing, monitoring, and controlling without the intervention of humans. The IoT applications are used by buildings managers to govern energy use and energy procurement and to maintain buildings systems. The BMS is based on the infrastructure of the existing Intranets and the Internet and therefore employs the same standard guidelines as other IT devices. The value in IoT application is in both the data and the computing devices. Gathering data from more building services and equipment offers a more granular view of exactly how each building is performing. These will develop the Internet of Buildings (IoB) applications. These IoT applications will decrease the need for human intervention to manage the complexity and the amount of data will improve exponentially. The IoB requires interoperability and seamless data interchange between networks of buildings, external utilities, different subsystems in a building, various smart equipment, and increased interface with building stakeholders.

The IoT facilitates connecting and monitoring assets from virtually anywhere for the smart grids and energy sector using the interconnected computing devices and utilities. Energy consumers/prosumers have the opportunity and accessibility to improve energy efficiency and energy use. The smart grid is significantly altering the way businesses operate. Using IoT technology, utilities are equipped to generate power more efficiently, reduce emissions and management costs, improve operations, and restore power faster, while operators are able to immediately identify outages, allowing for increased efficiency to manage responses.

IoT technology extends the monitoring and control of the plant and animal products during the whole life cycle from farm to fork. The concern will be in the future to design architectures and implement algorithms that will support each object for optimal behavior, according to its role in the Intelligent Farming system and in the food chain, lowering ecological footprint and economical costs and increasing food security. The smart cold chain logistics domain possesses high complexity and high risks because food and pharmaceutical goods are exposed to increasingly long and complex supply chains with many dangers of poor temperature control, delays, and physical mishandling. The prototype increases the transportation process by monitoring the state of the products during transportation and by early warnings when the goods are not stored according to clients’ requirements.

Wearables are integrating key technologies such as actuating, communication, nanoelectronics, low power computing, visualization, organic electronics, sensing, and embedded software, into intelligent systems to bring new functionalities into clothes, fabrics, patches, watches, and other body-mounted devices.

The IoT makes use of synergies that are generated by the linking of Consumer, Business, and Industrial Internet Consumer, Business, and Industrial Internet. The overlap creates the open, global network linking data, people, and things. This intersection leverages the cloud to link intelligent things that sense and transmit a broad array of data, helping to develop services that would not be obvious without this level of connectivity and analytical intelligence. The use of platforms is being delivered by transformative technologies such as things, cloud, and mobile.

The impulsive surrounding advancing IoT programs are very complex and issues such as systems integration, enablement, value-added services, network connectivity, and other management functions are all requires that generally must be utilized when the end-users seek to link smart edge devices into complex IoT applications. From the end-user standpoint, open relationships between various stakeholders in the IoT value chain are the best available means to employ these complexities. The technological trend is a move from systems where there are multiple users/people per device, people in the control loop of the system, and the system providing the ability for people to interact with people. The IoT offers a new epitome where there are multiple devices per user; the devices are things that are connected and interacting with other things. The communication will be with a variety of continuum of users, things, and real physical events.

Also Read: Applications Of Internet Of Things (IoT) In Engineering