In November 2014, E-commerce giant Amazon announced the launch of Alexa, a voice-controlled virtual assistant whose task is to transform words into action. It caught the attention of tech enthusiasts and the general populace alike. The inclusion of Samuel L. Jackson’s voice in Alexa was the talk of the tech town.

Recent years have witnessed a climactic change in the way technology interacts with humans. Alexa happens to be just that one card out of the deck. From Tesla’s cybertruck to internet giant Facebook’s EdgeRank and Google’s PageRank has called for both awe and a little bit of commotion within the tech community. The driving force behind such innovations can be put under a single umbrella term — Artificial Intelligence or AI.

Artificial intelligence (AI) can be defined as — the simulation of human intelligence in machines, especially computer systems and robotics. The machines are programmed to think and mimic human actions such as learning, identifying, and problem-solving.

Although AI has burst into the scene nowadays, the history of AI goes way before the term was first coined. It is safe to say that the principle is derived from the Automata theory and found references in many storybooks and novels. Early ideas about thinking machines emerged in the late 1940s to ’50s by the likes of Alan Turing or Von Neumann. Alan Turing famously created the imitation game,
now called the Turing Test.

After initial enthusiasm and funding on machine intelligence until the early 1960s,entered a decade of silence. It was the period of reduced interest and funding on research and development of AI. This period of decline is known as ‘AI Winter.’ Commercial ventures and financial assistance dried up and AI was put on hibernation for the said period.

The late 1970s witnessed a renewed interest in AI. American machine learning pioneer Paul Werbos devised the process of training artificial neural networks through backpropagation of errors. In simple terms — Back Propagation is a learning algorithm for training multi-layer perceptrons, also known as Artificial Neural Networks.

The neural networks consist of a set of algorithms that loosely mimics a human brain. It means much like a human brain; it is designed to interpret sensory data, cluster raw inputs, and classify them accordingly.

1986 saw the backpropagation gaining widespread recognition through the efforts of David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams. In 1993, Wan became the first person to win the international pattern recognition contest with the help of the backpropagation process.

Since the emergence of computers and artificial intelligence, computer scientists have drawn parallels between these intelligent machines and human minds. The comparison reached a pinnacle when, in 1997, an information technology company, IBM, created a computer known as Deep Blue to participate in a chess match with renowned chess master Gary Kasparov. The match went on for several days and received massive media coverage. After a six-game match, Gary Kasparov secured a win, Deep Blue secured two wins and rest three draws. The highlight of the spectacle, however, was the ability of machines to push forward the boundaries and lay down a new benchmark for computers.

Deep Blue made an impact on computing in many different industries. It enabled computer scientists to explore and develop ways to design a computer to tackle complex human problems with the help of deep knowledge to analyze a higher number of possible outcomes.

The rise in popularity of social media with Facebook saw the implementation of AI/ML in a wide array of applications. One prominent characteristic was the use of DeepFace. As the name suggests, DeepFace is a deep learning facial recognition system designed to identify human faces in digital images. DeepFace was trained on four million images uploaded by Facebook users and is said to reach an accuracy of 97%. Not so long after, NVIDIA launched Generative Adversarial Network (GAN), which is a class of machine learning designed to generate new data with the same inputs provided. The portraits created by GAN is so realistic that a human eye can be fooled into thinking it as a real snapshot of a person. GAN has seen widespread usage in the creation of celebrity faces. Google’s popular doodles are an outcome of the GAN system.

The advent and rise of AI, however, has generated quite of bit of negative speculations as well, owing to recent developments in the said field. Some key concerns are as follows:

•  In 2016, Hong-Kong based Hanson Robotics introduced Sophia to the world. Sophia is a humanoid robot adept in social skills that can strike a conversation, answer questions and display more than 60 facial expressions. As much as it looked futuristic, the eeriness of the entire scenario did strike a discomfort among the masses. After all, machines being humans is something people are not accustomed to. The increasing use of robots and robotic science in the manufacturing industry is striking a rather uncomfortable nerve worldwide, as it comes with the replacement of the human workforce.

• It has been noticed that only a handful of industries gain immense help from AI. This has mostly been the IT sector and specific manufacturing industries. As a result, not every party is not willing to invest in AI technology and it remains to be seen how the situation unfolds in such a scenario.
• The last two decades witnessed a blossoming of interest and investments in AI. The emergence of AI algorithms, coupled with massive amounts of data and its ability to bend/manipulate them, is one of the most significant factors that artificial intelligence has reached where it is today. The development of deep learning is another for resurgence out of AI winter. However, with all the investments, interest, and funding, can AI live up to its hype, or is it heading towards another AI winter due to over-exaggeration, overpromising, and seemingly under-delivery of it said capabilities. It remains to be seen.

While there are certainly lots of speculations for AI, we expect that the next AI winter would not come. Another AI winter is possible if we repeat the past circumstances. As for now, AI is becoming a part of our daily lives. It is in our cars, phones, and other technologies we use on a day-to-day basis. It is common to interact with AI regularly, whether it is a helping chatbot, personalized ad or better movie show/TV suggestions. AI is too much integrated into our lives and only time will tell where it heads.

Outsourcing has remained an integral aspect of striking deals between engineering and design firms. While it has been growing at a solid pace each year, several companies have taken the route to insource a part of their formerly outsourced services portfolio.

Insourcing is the practice of assigning a task to an individual or group inside a company. The work that would have been contracted out is performed in house. 

Insourcing is entirely opposed to outsourcing where the work is contracted outside. Insourcing encircles any work assigned to an individual, team, department or other groups within an organization. It is a task or function that a firm could also outsource to a vendor, being directed in-roads. It often involves getting specialists with relevant expertise to fill temporary needs or train existing professionals to execute tasks without the need to outsource the same. The group of professionals could either be direct employees of the organization or hired expertise from outside third party vendors.

A perfect example can be put in this way – a company based in India opens a plant in the United States and employs American workers to work on Indian products. From the Indian perspective, this is outsourcing, but from the American perspective, it is insourcing.

Causes of Insourcing

The leading reasons for insourcing include:

• A management mandate to make changes in corporate sourcing strategy
• To provide a remedy for a turbulent outsourcing relationship
• To obtain the right mix of in-house and outsourced services based on current business goals
• Mergers and acquisitions can also influence insourcing decisions. A decent post-acquisition integration plan should include a common sourcing strategy between the two companies, which may ask for the outsourcing of functions that are in-house at one company and the insourcing of a task that was previously outsourced at the other
• Insourcing enables companies to have control over decision-making and the ability to move more quickly and precisely

Reasons to Insource

• Boosting business agility
• Transformation needs secure integration with the business
• Knowledge is now available and increasingly democratized
• Cybersecurity threats
• Providing a platform to nurture talent

While executing an insourcing project can be achieved, it is essential to know that insourcing a service can be more complicated than outsourcing the same. The transition may require rebuilding services and leveraging capabilities from ground level that were once wholly owned by the service provider, which can turn out to be more complicated than expected.

Both insourcing and outsourcing are feasible ways of bringing in labor or specialty skills for a business without hiring permanent employees. When it comes to selecting between outsourcing and insourcing, several entrepreneurs cannot decide what is best for them. Before jumping on to the differences between these two business practices, we need to check the definition of the terms.

Insourcing is the practice of assigning a task or function to an individual or group inside a company. The work that would have been contracted out is performed in house. 

Outsourcing is the act of assigning a task or function to a third party vendor instead of having it performed in-house.

Differences between Insourcing and Outsourcing

• Insourcing helps to track the development process and puts control over the quality of the work, while in the case of outsourcing, it becomes difficult to trace the quality of work.

• There is very minimal risk in insourcing, as one can have complete supervision over intellectual property (IP). In outsourcing, the entire task is in the hands of an outside third party. In case IP is leaked, it proves awful as investments on research, people and development work go in the vain and outside party claiming the idea as theirs.

• Insourcing helps in evading intermediaries’ costs like fees and commissions. Insourcing also drives to point other cost exponentials such as incorporating and utilizing third-party vendors who offer value-based pricing.

• As insourcing helps in keeping track of task and workforce, it runs hand in hand with development squad which in turn helps in keeping an eye on every move in the business, finding problems and resolving them. While in outsourcing, one lacks to track when the problem arises and how it’s fixed.

• In outsourcing, there are possibilities of miscommunication as the outsourcer and outsource vendor are in different places. The information goes from head management, and then, they commune it to outsource provider’s managers, who will lastly convey it to employees. This arduous and lengthy process has a risk of miscommunications. However, insourcing cancels out such possibilities. The miscommunication aspect is reduced in insourcing, as there is direct communication with employees.

• Outsourcing a project overseas might face a few issues due to the different time zone and cultural factors. A vendor might have varying physical outsources, various techniques, design, and engineering. There is a big chance of communication problem due to different time zone. In insourcing, the assigned team will easily decipher the requirements, design, and engineering to produce a product as per nativity.

• Various projects require complete confidentiality of data, which cannot be outsourced to a third party vendor. In that case, it is feasible to bring in their resources over to the project location, keeping the confidentiality intact while introducing expertise.

Insourcing is more preferrable when the business requirement is for a limited time or temporary or involves little investment. Outsourcing weighs more when businesses need to cut costs while still in need of expert professionals.   

Insourcing software development has turned out to be an effective way for tech firms to boost business. Not to mention that is the exact opposite of outsourcing with similar intents. But like any business strategy, preparation and execution is necessary and are crucial for a successful endeavor. Choosing an insourcing partner requires as much meticulous planning and careful observation as in the case of outsourcing. Following are the tips on choosing the right insourcing partner for your business.

Establish insourcing goals

This is the most critical step a company can take while choosing an insourcing partner. The scope of work, the billings, the project requirements has to fall under the capability of the insourcing partner. The responsibility of the partner is to maintain a high standard of quality.

The Right team size

Many companies overlook this consideration while they are looking into insourcing options, but it’s one of the most crucial factors in the successful completion of an in-house project. Make sure the vendor partner has the right blend of expertise and number to cater to your requirements.

Work Experience

Find out if the vendor supplied workforce has the right experience and expertise in delivering services similar to the one you plan for insourcing. This includes several projects executed, types of clients worked for, and function expertise for knowledge-intensive tasks. Assess the experience and qualifications of the management team, project managers, and other team members of the vendor company. Before entering into a long-term or substantial contract, interacting with the proposed team members before the commitment ensures fitment between requirement and the team chose to execute it.

Financial Stability

This factor is also overlooked to a great extent. It is essential to make sure that the vendor partner has sufficient working capital and is financially secure. There have been cases where the insourced workforce is not paid correctly by their employers. This, in turn, affects their productivity. This is a classic case of ergonomics.

Privacy and Confidentiality

Numerous projects emphasize confidentiality factor. There might be instances where a task cannot be outsourced merely because of the sophisticated nature and business goals entangled with it. But then, lack of workforce and budget issues drive a company to go for the insourcing route. This helps in keeping the work in-house and private while supplying it with necessary measurements.

There might be a variety of other factors out there depending upon client preferences and conditions. Irrespective of the vendor one chooses, starting a pilot project with a small team is always feasible to assess the scope of the outcome on the long run and scale-up with time seeing the fitment of the vendor with the business objectives and culture.

When outsourcing projects or insourcing tasks, organizations face a very crucial question about billing. Working with outsourced development team means that there are a few elementals that need to be sorted out from the beginning. It is because each project is different in its regard and comes up with its own set of requirements.

When a customer signs a deal with a software development company, they sign a billing agreement. The pricing model used depends mainly on project requirements. Two popular billing models are — Fixed-price Contract and Time and Material Contract. Selecting the right contract agreement is a vital step when outsourcing software development. Consequences of a wrong choice may yield unexpected outcomes.

Each type of contract has its pros and cons; hence, choosing any one of them may be a complicated task. The option that is well suited for one project may not be the ideal for another one. This article emphasizes on the advantages and disadvantages of these pricing models and explains which is better in what condition.

Fixed Price Contract

The fixed-price agreement is a type of contract where the service provider is accountable for completion of the project within the agreed sum in the contract.

In a Fixed Price model, the total budget on the project is set before development starts and remains unchanged. Plus, the exact deadline must be approved before the development starts. The contractor will bear the risks for late execution of works.

It is a practical choice in those cases, where requirements, specifications, and rates are highly predictable. The client should be able to lay down his clear vision of the project with the contractor to ensure appropriate final results.

When to use a fixed price contract:

• Clear requirements and deadlines
• Limited or fixed budget
• Limited project scope

Fixed Price advantages

• Usually requires clear deadlines and figures to be set to the budget. Planning expenses 1 to 3 months provide accurate statistics.
• Regular project management communication with the contractor ensures scope compliance and eliminates the possibility of surprises.
• Payments to the service provider count on the percentage of work performed. There is little involvement in such workflows since expectations are transparent and preset.

Time and Material Contract

Time and material (T&M) contract is the type of contract where the contractor is charged for the number of hours spent on a specific project, plus costs of materials.

Time and material contracts are much different from Fixed-Price because they involve billing clients for what they get. A time and material contract charges clients based on an hourly rate for all labor, along with the costs of materials. This type of arrangement might present some risk to the budget, but factors such as flexibility and opportunity to adjust requirements, shift directions and replace features prove to be very beneficial nonetheless.

In this model, the customer has a more significant role in the development of the software solution and bears all risks related to the project. The length of responsibilities that the client carries through the whole development process with time & materials is much higher than with fixed-price projects.

When to use T&M price contract:

• Long-term projects
• Full project scope not established
• Flexibility to modify the range with varying requirements

Time and Material advantages

• T&M contracts allow businesses to modify the scope of work, revise materials or designs, shift the focus or change features according to project requirements.
• There can be an established general goal that can be achieved, however knowing how it’ll be achieved is not so important beforehand.
• Opting for T&M contract process helps to save time and start projects immediately.

Processing geometric inputs play a crucial role in the product development cycle. Ever since the introduction of complex algorithm libraries, the NPD landscape has changed drastically, and for good. Typically, a well suitable library streamlines the work process by executing complicated tasks using a wide array of functions.

An algorithm library basically works on the principle where it is fed with specific instructions to execute in a way with functionalities customised with it. For example, in manufacturing industry; there is a term known as point cloud library and it holds its expertise in converting millions of point cloud data into mesh models.

There are particular algorithms to perform numerous perplexing tasks. There are platforms that use specific and unique functionalities and programming to get the job done. Manufacturing requirements, end product objectives lay down the necessities for choosing a particular algorithm library. This article sheds a light on 6 key factors to consider while selecting any algorithm library.

Required functionality

Once data has been fed and stored, methods for compressing this kind of data become highly interesting. The different algorithm libraries come up with their own set of functionalities. Ideally, functionalities are best when developed by in-house development team, to suit up in accordance with design objectives. It is a good practice to develop functionalities to address complex operations as well as simple tasks. It is also essential to develop functions which might be of need down the line. In the end, one’s objective defines what functionality laced algorithm library will be in use.  

Data Size and Performance

A huge data can be challenging to handle and share between project partners. A large data is directly proportional to a large processing time. All the investments in hardware and quality connections will be of little use if one is using poor performing library. An algorithm library that allows for the process of multiple scans simultaneously has to be the primary preference. One should also have a good definition of the performance expectations from the library, depending on your application whether real time or batch mode.

Processing speed

Libraries that automate manual processes often emphasize on processing speed, delivering improvements to either the processing or modeling. This allows for faster innovation and often better, yet singular, products. As witnessed in the case of point cloud, the ability to generate scan trees after a dataset has been processed greatly improves efficiency. A system will smooth interface that permits fast execution, greatly reduces the effort and time taken to handle large datasets.

Make versus Buy

This situation drops in at the starting phases of processing. Let us take an example of point cloud libraries. Some of the big brands producing point cloud processing libraries are Autodesk, Bentley, Trimble, and Faro. However, most of these systems arrive as packages with 3D modelling, thereby driving up costs. If such is the case, it is advisable to form an in-house point cloud library that suits the necessities. Nowadays, many open source platforms give out PCL to get the job done which has proven to be quite beneficial.

Commercial Terms

The commercial aspect also plays a vital role in while choosing an algorithmic library. Whether to opt for single or recurring payment depends upon the volume and nature of the project.  

There are different models to choose from, if one decides to go with licensing a commercial library:

A: Single payment: no per license fees, and an optional AMC

B: Subscription Based: Annual subscription, without per license fees

C: Hybrid: A certain down payment and per license revenue sharing

Whatever option you select, make sure there is a clause in the legal agreement that caps the increase in the charges to a reasonable limit.

Storage, Platforms and Support

Storage has become less of an issue than what it was even a decade ago. Desktops and laptops with more than a terabyte of capacity are all over the market. Not every algorithm library requires heavy graphics. Investing in a quality graphics card is only important if your preferred library demands heavy graphic usage. That doesn’t mean investing in cheap hardware and storage systems available. A quality processor with lot of RAM is decent if the processing task is CPU and memory intensive. Another point to look into, is the type of platform or interface to be exact, the algorithm library supports. Varied requirements call for varied platforms such as Microsoft, Mac, and Linux. The usage, and licensing should be taken into account before selecting an interface.

Last but not the least, it is to mention that the inputs from customers are highly significant and there has to be a robust support system to address any grievance from the customer side. Having a trained support staff or a customised automated support system must be given high priority.

At the starting phase of developing an application, the primary question usually comes like this—whether to make it an add-on application or a standalone application?

Before we get into the details, we need to understand what exactly these two terms mean in the computing world.

An add-on (also known as addon or plug-in) is a software application, which is added to an existing computer program to introduce specific features.

As per Microsoft’s style guide, the term add-on is supposed to represent the hardware features while add-ins should be used only for software utilities, although these guidelines are not really followed as terms are mixed up quite often. When a program supports add-ons, it usually means it supports customization. Web browsers have always supported the installation of different add-ons to suit the tastes and topics of different users by customizing the look and feel of that particular browser.

There are many reasons for introducing add-ons in computer applications. The primary reasons are:

• To introduce abilities to extend an application by enabling third-party developers to create variety of add-ons
• To support new features
• To reduce the size of an application
• To separate source code from an application because of incompatible software licenses

Usually, the host applications operate independently, which makes it possible for developers to add and update add-on features without impacting the host application itself. A host application doesn’t depend on add-ons but on the contrary, an add-on depends on the host application. Add-ons usually depend on the services provided by the host application and cannot operate by themselves.

A Standalone application is the type software that doesn’t comes bundled with other independent software features. In simple words, a standalone application does not require any separate software to operate.

A stand-alone application deploys services locally, uses the services, and terminates the services when they are no longer needed. If an application does not need to interact with any other applications, then it can be a stand-alone application with its own exclusive local service deployment. Services locally deployed by this application are not available to any other application.

A standalone application needs to be installed on every system which makes it hard to maintain. In the event of a system crash or a virus attack, when a system needs to be replaced or reinstalled, the application also needs to be reinstalled. The access to the application is limited only to the systems that have the application installed.

Standalone applications can never be kept online, and remote availability of data is practically impossible. However, there are situations where standalone application is the best choice. Here are a few:

• Text mode printing on pre-printed stationary, which browsers fail to do
• Where data security is very high and you don’t want the data to travel on the wire at all
• Design applications which need very high responsiveness and at the same time work on big data structures
• Printing on legacy continuous stationery
• No need of networking, application is needed only on a single system
• More hardware support like barcode printers, webcam, biometric devices, LED Panels, etc.
• More Operating System level operations like direct backup to external devices, mouse control, etc.
• Creation and manipulation of local files

As the development of software makes its progress, there comes a stage where it needs to be evaluated before concluding it as the final output. This phase is usually known as testing. Testing detects and pinpoints the bugs and errors in the software, which eventually leads to rectification measures. There are instances where the rectifications bring in new errors, thus sending it back to another round of testing, hence creating a repeating loop. This repeated testing of an already tested application to detect errors resulting from changes has a term — Regression Testing.

Regression testing is the selective retesting of an application to ensure that modifications carried out has not caused unintended effects in the previously working application.

In simple words, to ensure all the old functionalities are still running correctly with new changes.

This is a very common step in any software development process by testers. Regression testing is required in the following scenarios:

• If the code is modified owing to changes in requirements
• If a new functionality is added
• While rectifying errors
• While fixing performance related issues

Although, every software application requires regression testing, there are specific points that apply to different applications, based on their functioning and utility. Computer-Aided design or CAD software applications require specific points to keep in mind before undergoing regression testing.

Regression testing can be broadly classified into two categories, UI Testing and Functionality Testing. UI testing stands for User Interface which is basically testing an applications graphical interface. Numerous testing tools are available for carrying out UI testing. However, functional testing presents situation for us. This content focuses on the points to take care while carrying out functional regression testing.

Here are most effective points to consider for functional regression testing:

• It is important to know what exactly needs to be tested and the plans or procedures for the testing. Collect the information and test the critical things first.
• It is important to be aware of market demands for product development. Document or matrix should be prepared to link the product to the requirement and to the test cases. Matrices should be modified as per the changes in requirement.
• Include the test cases for functionalities which have undergone more and recent changes.
  It’s difficult to keep writing (modifying) test cases, as the application keeps on getting updated often, which leads to some internal defects and changes into the code which in turn might break some already existing functionalities.
• It is preferred to run the functionality testing in the background mode (non-UI mode) because often it is faster and eliminates problems associated with display settings on different machines.
• One needs to lay down precise definitions of the output parameters that are of interest. Anything from the number of faces, surface area, volume, weight, centre of gravity, surface normal, curvature at a particular point etc. It is always a good idea to have a quantifiable output parameter that can be compared.
• It is often advisable to develop a utility to write the parameters that are of interest in an output file it could be text, CSV or xml file.
• Creating baseline versions of output data files is a good idea to visually see every part for which the baseline data is created.
• Developing automation script enables the entire test suite to run without any manual intervention and the results can be compared.
• Compare the output data generated with the baseline version, for every run of test case, for it is very important to keep in mind that if there are doubles or floats in the output data, tolerance plays a very important role.
• Some areas in the application are highly prone to errors; so much that they usually fail with even a minute change in code. It is advisable to keep a track of failing test cases and cover them in regression test suite.

Failure to address performance issues can hamper the functionality and success of your application, with unwelcome consequences for end users if your application doesn’t perform to expectations.

In any software development process, the methodology involved is more or less the same. The most generic requirements are developers, preferred programming language, testers and carefully planned set of actions to perform. The same can be applied to development of CAD software as well.

Having CAD software that can actually meet product development needs is an obvious necessity. Although, there is a lot of common ground between a CAD software development project and a regular software development project, there are criteria very specific to CAD software development projects which needs to be addressed.

Let us take a walkthrough:

• Acceptance Criteria

  Acceptance criteria are a list that mentions user requirements and product scenarios, one by one. Acceptance criteria explain conditions under which the user requirements are desired, thus getting rid of any uncertainty of the client’s expectations and misunderstandings. However, defining acceptance criteria is not simple, but has its complications. Also, it is not convenient to expect a 100% pass rate. In such case, an ideal way is to have a set of test cases with defined input and output data.

• Algorithmic Complexities

  To successfully develop a complex product, two critical questions must be answered, how to develop the right product and how to develop the product right.Unlike some of the other problems like interest rate calculations or workflow management system, there is not a defined set of steps that results in the final answer. There are often multiple algorithms for a single issue and the situation becomes more complicated when a particular algorithm, deemed to be perfect for a given situation, may not perform that well in a different scenario, which often leads to trade offs.

• Tolerances

  Tolerance is one of the factors to evaluate product quality and cost. It has a significant role. As tight tolerance assignment ensures design requirements in terms of function and quality, it also induces more requirements in manufacturing, inspection and service that results in higher production cost. Most of CAD data works on variables that are doubles and floats and Floating point precision, Tolerance plays a very important role in the algorithms. When using data from other systems say STEP file from other source, if there is a mismatch in the tolerance, the destination system can cause lot of issues.

• Risk of Regression

  Adding a new functionality or improving an algorithm always has a risk of impacting the test cases that were working before the fixes. One should always develop a robust test suite for catching regressions while carrying out testing. To create a regression test case suite one must have thorough application knowledge or complete understanding of the product flow.

• Interoperability

  The quick emergence of varied CAD software has led designers to democratize, leading to the usage of multiple CAD systems in the design process, thus challenging the CAD interoperability aggressively. Different suppliers require different CAD platforms. It depends on many factors, primarily the nature of the task and product upon which it has to work. Merging different CAD data together without affecting the design intent is quite the hassle. Although, a lot of software these days support different CAD files, there are instances, where the particulars of a project has made the product confined to that one CAD software. Interoperability eases up extra work and whether to make your own software compatible with other, is a decision that should be seriously taken into account.

For starters, digitization is converting of analog/physical things such as paper documents, microfilm images, photographs, sounds and more into digital (bits and bytes) version. So it is simply converting and/or representing something non-digital into a digital format which then can be used by a computing system for numerous reasons.

Sometimes a paper document gets destroyed after having digitized, sometimes we capture the sound and images in the form of video of your presentation at an event, the digital format continues to exist while your voice and physical presentation during that presentation are gone forever. Digitizing doesn’t means replacing the original document, image, sound, etc.

Another synonymous term is ‘Automation’ which more or less means the same. The conversion of physical data into intangible format has its benefit and has revolutionized paperwork in its own way.

Benefits of Digitization

• Streamlining of process, which results in delivery of information to the right person at the right time, optimization of the processing time and improvement in overall productivity and efficiency.
• Smooth management, storage & control of documents; protection of records in physical form and reduction in the risk of losing documents.
• Digitization process ensures the continuous availability of information.
• Elimination of manual search
• Reduction in storage costs

5 ways digitization is helping the business

Automation/Artificial Intelligence

There have been debates about automation and development of artificial intelligence (AI) over the last couple of years. All credits to movies and their takes on AI. Some eminent minds have also predicted its dark future. However, AI has already changed the business world with companies gradually automatizing work and other sorts of activities. Almost 85% of industry leaders believe automation will allow their companies to obtain or sustain a competitive advantage.

Flexibility of working hours

With all the data and information being stored on digital media and devices; digitization has made it possible for us to transform it and access it from anywhere. As a result, we can adjust our work schedule to our personal needs and lifestyle. We can choose how to work and when to work, and we owe it to digitization.

Innovation

We all know, innovation helps companies come up with groundbreaking ideas, use special tools and business applications for organizing & managing work, reach wider audience and create a better product. Digitization is not only about transforming physical data into digital format, but also about using it and finding new ways of developing/enhancing them.

Communication

The lack of right information transfer leads to misunderstandings and conflicts. Without proper communication, a business cannot thrive. Communication has always been one of the most important aspects of our lives. Fortunately, there are tools and channels that enable smooth exchange of information. There are tools that facilitate the exchange of thoughts, ideas and opinions such as blogs, websites, conferences and business meetings. Digitization has made it possible to propagate information while providing ready access to information, thereby, consuming less amount of time.

We all know reverse engineering is an economical approach towards product development & innovation which is often utilized by manufacturers to evaluate and redesign competitor products. The method requires understanding the product design, system integrity and the manufacturing processes involved to realize the potential required to build a similar or an improved version of the product. The reverse engineering technique is best suitable for producing design data and related technical manuals for products that no longer have any design information available.

The entire work-process involves engineers studying every single design feature, associated manufacturing processes and tools needed for product development and storing information using CAD tools. After digitizing the entire information, suitable design modifications are carried out as per requirements.
However, to get things right one should have an efficient and dedicated engineering team, right software and hardware tools, etc. which seems difficult to have within the organization always.

Here comes the advantage of outsourcing reverse engineering projects where the activities can greatly reduce the cost of product development and burden on the engineers who can, then, put full emphasis on developing innovative design solutions for the product.

If one still questions outsourcing, some of the important benefits to outsourcing reverse engineering projects are mentioned below.

• Outsourcing can bring in a global pool of talent with the myriad of innovative ideas that can assist in product design and development without investing in infrastructure and resources.
• As the in-house resource can focus on R&D, it greatly helps in improving the productivity of an organization.
• Product development time reduces considerably.
• Hiring an outsourcing partner who matches requirement scale greatly enhances the organization’s capability.
• RE outsourcing presents a scope to develop the product at a competitive price since the development cost is considerably less.

As much feasible Reverse Engineering and its outsourcing sounds, there are specific steps to follow and factors to keep in mind. Few crucial points to discuss when outsourcing RE are as follows:

• The objective of reverse engineering; as your provider needs to know your goals to suggest a rather cost-effective solution
• Whether reverse engineering has to be for design intent or as-built which, yet again, depends solely on the organizations end goal
• What kind of measurement data should be approached and to what extent the accuracy of measurement should be implemented, depending on organizational planning,
• For obtaining the most accurate measurements, the original object is often disassembled or even destroyed. Whether to go ahead with such a step or keep the original product intact for future reference is something an organization should carefully decide on
• What tools to be used for digitizing the final date, like desired software with its version to suit the complete development ecosystem

Once the decision to outsource the reverse engineering process has been finalized, the next important step to consider is, choosing a vendor. Responsive and efficient vendors make all the difference. Finding a professional vendor with a high level of efficiency and even heightened work ethic is a complex but satisfying process. Be aware that once you are engaged with a vendor, it becomes little difficult to break the deal and discontinue ‘business’ with the existing vendor. So choose carefully but commit completely after the contract.

When a vendor has been finalized, organization issues a request for quotation (RFQ). RFQs are created to invite suppliers to a bidding process to bid on specific services/products. The organization should also take a legal approach and have the non-disclosure agreement (NDA) signed by the service provider. This is done to prevent unlawful, authorized distribution or illicit adoption of the product.

Now that the legal approach has been taken and paperwork has been taken care of, the organization sends the physical product to the service provider or the scanned files of the same; which solely depends on company needs. The vendor is also supplied with measurement specifications and related industry standards to follow. Eventually, the vendor creates digital CAD formatting required software and sends them back to the organization for further investigations on design modification or innovation.

For manufacturers, reverse engineering is a profitable strategy in today’s competitive scenario; however, outsourcing it brings along the other benefits as well that ensures product development process remains cost-effective.