Introduction Figure. The accuracy from the AI system is

IntroductionProductdesign Product DesignProduct design in product development creates a design inaccordance with the technical, manufacturing, ergonomic, market-related andfunctional requirements and specifications. Dependent on the company this isachieved through different procedures and systematic checks to ensure theproduct meets these requirements and specifications to ensure their success.

Computer Aided Design (CAD) and Product Data Management (PDM) have led the wayin the advancement of Product Design in recent years with the requirement ofmore integrated design. These methods however still use traditional designmethods and are not fully integrated. https://pdfs.semanticscholar.org/ad48/d28bb04c196036f743c89f5e519ff7b74924.pdf1/1/2018https://link.

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springer.com/chapter/10.1007%2F978-1-4020-7829-3_321/1/2018https://uxdesign.cc/how-ai-will-impact-your-routine-as-a-designer-2773a4b1728c  1/1/2018ArtificialIntelligence Impact on PDThere is currentlysome AI integration in product design. Artificial Intelligence is applied toproduct design in Monozukuri, the Japanese way of manufacturing.

The MonozukuriAI framework was developed on the cloud as a system to facilitate efficientcollection of product development data and for managing and leveraging learningmodels from such data. With the Flexile Technical Computing Platform (FTCP),Fujitsu’s integrated development platform, the Monozukuri design developmentenvironment will provide various design tools with new enhanceddesign-assisting features. Using this system, there is the potential toestimate the number of layers in PCBS. This is done using an algorithmoptimised based on PCB designer data. Ordinarily this would be a difficult andtime consuming task even for skilled designers.

The learning model uses thedata in a regression analysis method from the circuit design stage only whichis refined down to similar product and PCB type before an algorithm isoptimised. This allows for an estimation to be made on the number of layersother than signal layers. This allows for an evaluation of the accuracy of thealgorithm made by the AI system to be evaluated as seen in the Figure.  The accuracy from the AI system is comparableto the accuracy of the worker but is derived in a faster time. This use of AIis a good example of how the integration into the product design field is timesaving as well as resource saving as the designers who would have previouslyhad to solve this would’ve spent their time solving the issue. https://pdfs.

semanticscholar.org/ad48/d28bb04c196036f743c89f5e519ff7b74924.pdf      1/1/2018Although we have seen successes, we have also seen failuresin terms of Artificial Intelligence’s involvement in design.  The Grid was a website development and designsystem powered by AI where the website was built without the need of adesigner. The AI aspect is mainly in the presentation of content. A customdisplay form is selected for the content to be published in automatically bythe AI segment. This is done by analysing pictures from which the colour valuesand extracted, texts placed and teasers produced, ensuring the design rules aremet. The limitations of the system are vast as the system remains basic.

Therewas large disapproval after the first websites were released with a generalconsensus that designers should not fear for the jobs as of yet. The use of AIhere shows the limitations at present with its use and that further developmentof the use of AI in product design will be positive but also that thecommercialisation stage of its integration is not yet here. http://goati.info/https://www.

denkwerk.com/en/blog/designing-websites-with-ai-thegridio.htmlFutureAI in PDConclusionMarket IntroductionMarket Introduction is the introduction of new products intothe market place. Market introduction is a careful balance of understanding themarket place and ensuring the products strategic placement in the market isprofitable. An understanding of the competition the product faces can beestablished through a strengths, weaknesses, opportunities and threats (SWOT)analysis to decipher how the competition have approached their product release.

This is important even if the product is entirely unique as it also includescomprehending what the prospective customer is anticipating. Consideration ofthe ideal target market, unique advantages of the product, marketing strategiesand tactics as well as the approach should be undertaken to ensure the bestpossible introduction of a successful product into the market. https://www.entrepreneur.com/article/76364  1/1/2018The revolution of Artificial Intelligence in Marketing hasbeen encouraged due to the availability of affordable and accessible dataanalysis tools and extensive datasets. With these new tools available, a newdata-driven approach to marketing decision making is thought to be within reachover the next few years. Although currently such tools are available tomarketing analysers, AI is required to help integrate between the marketingplatforms, datasets and available tools.

There is also the difficulty ofintegrating a vast amount of different tools, sources and platform packages toprovide an insight but with the influence of AI it’s believed that changes willbe made to incorporate these into a more manageable system. AI will take theoutputs from the various data sources and provide an analysed integrated viewof marketing positions. This will be a time saver for large corporations. We do have examples of AI Marketing available to uspresently. Netflix using predictive analysis to finesse recommendations for itsaccount holders. This is based on clustering algorithms to continually improvesuggestions based off of the customer’s choices so that they can make the mostof their subscription. This ensure that the customer is continually satisfiedas new products are made available to them so their subscription will continue.

The choices, however, based off this algorithm aren’t always correct and thecustomer is provided with products that don’t satisfy their need. This showsthat although AI is integrated into our current services, further work on theanalysis of human preferences is required.The future of AI in Marketing is more integration of the useof algorithms to save time and efforts which are utilised elsewhere in areasnot yet integrated. AI based sales and marketing automation are also set toaccelerate in the future. AI will help companies build a corporate culture withcustomer focus at the forefront which will help optimise marketing goals suchas personalisation, customer behaviour and engagements as well as increasingaccuracy over predictive analyses.  Someapplications that are being investigated within the next 10 years includefurther development of the virtual assistant such as siri to become moreintelligent and interactive, more personalised marketing campaigns as well asmore natural language processing into gauging customers moods and intents.

https://onlinesales.ai/blog/ai-future-marketing/ Integration of AI comes at a risk as data is never perfectand all interpretations of patterns and datasets, done by either marketers orAI, will still be subject to bias and could be misled if data is incorrectlyanalysed. And although AI powered tools and devices will save time, the humanpart of a company’s relation with a customer is also important so spending timewith customers will become more valuable the more digitalised the processbecomes. As the process becomes more digitalised, the marketing workforce willhave also have to have a higher level of digital literacy to compensate.

https://econsultancy.com/blog/67745-15-examples-of-artificial-intelligence-in-marketing1/1/2018https://www.forbes.com/sites/andrewstephen/2017/10/30/ai-is-changing-marketing-as-we-know-it-and-thats-a-good-thing/#72518951dc401/1/2018In terms of Marketing, the effect of the AI integration canbe seen at present but there are vast improvements and various other means ofAI that will be integrated into marketing in the next 10 years to improve theefficiency and accuracy of the data analysis available. Manufacturing FunctionsManufacturing Functions has been ever expanding since thefirst industrial revolution. The first, second and third revolutions saw theintroduction of mechanical production, mass production and automated productionrespectively. Now the fourth industrial revolution is upon us, building uponthe third revolution which aim to fuse the physical, digital and biologicaladvancements.

Through the use of the internet it’s expected that the manufacturingprocesses will revolutionise the way they make and ship goods. CurrentAI in ManufacturingFutureAI in ManufacturingOverallhttps://www.engineering.com/AdvancedManufacturing/ArticleID/15670/Bringing-Artificial-Intelligence-to-Manufacturing.aspxhttps://www.forbes.

com/sites/mariyayao/2017/08/08/industrial-ai-factories-of-future/#5a13bf84128ehttps://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond/https://www.forbes.com/sites/bernardmarr/2016/04/05/why-everyone-must-get-ready-for-4th-industrial-revolution/#48d7252e3f90http://www.telegraph.

co.uk/business/social-innovation/artificial-intelligence-future-of-manufacture/https://mitpress.mit.edu/books/artificial-intelligence-applications-manufacturingIncreasing Effect of Artificial Intelligence Operations Management is concernedEffect on Operations Management PositionsOperations Management is concerned with planning, organisingand supervising production, manufacturing and services.  It focuses on delivery of plans and ensuresthat inputs such as resources are turned into outputs as planned. https://www.readitquik.

com/articles/off-premises/how-ai-is-changing-the-face-of-operations-management/https://www.topmba.com/mba-programs/what-operations-managementConclusionanasin         Giveconsideration towards the impact upon the individual in the working environmentas well as the end-user consumer of the manufactured product or service.

25marksIntroductionTheorganisation of workWork OrganisationThe organisation of work will be impacted as for economicreasons numerous jobs will be carried out by intelligent software or machinesrather than humans. The reasoning behind the replacements is more betweenroutine and non-routine work rather than physical and cognitive work as AI hasthe ability to be developed for decision making but cannot reason like a humanso will only be able to perform routine work. There are differences in opinion about how much of an impact thesechanges will have on company structures. Restructure of Workers Alongside AI Thejobs at risk are primarily labour driven. Routine jobs would easily be replacedby those Replacement of Labour – Less work for labourers as AI would be capableRetrainingof Labourers and Re-evaluation of Education SystemWouldn’taffect skilled thought driven jobs – Quantative Analysis would be available toAI but not qualitative analysis such as emotions, experiences, trend etc. Wouldbe difficult for AI to make decisions in times of uncertainty. High risk jobs will not replace completely, even if thetechnical advances would allow the replacement as there are furtherimplications as well as benefits to those introductions.

An example of this isthe role of a bartender whose job is at 87% chance of being replaced as amachine could mix drinks and perform the other roles of a bartender. Theimplications of this, however, is the human interaction of the bar environment asthis will be removed if humans are replaced. In view of the occupational work structure and the legal,technical, ethnical and social barriers, only 9 to 12 per cent of employmentwill be at risk of being completely replaced. Other studies expect that AI androbotics are not job killers with the eliminated jobs being compensated for bynewly created jobs. For example, the German government assumes that theintroduction of Artificial Intelligence will create about 390,000 new jobs overthe next ten years in Germany. Newly created jobs will require the retraining of workers. Jaimovich and Siu, The Trend Is the Cycle: Job Polarizationand Jobless Recoveries (2012) 8 ff Bonin, Gregory and Zierahn, Übertragung der Studie vonFrey/Osborne auf Deutschland (2015) 18.

Ibid at 14 www.rolandberger.com/publications/publication_pdf/roland_berger_amcham_business_barometer_2.pdf,15 (last accessed on 22 September 2016). www.

buendnis-fuer-industrie.de/unsere-themen/digitalisierung(last accessed on 26 April 2016).Impact on ProductsQuality – less variable and higherPrice is cheaper due to labour cost decreases – more iswithin reach of the common purchaser due to price decrease, upgrade marketwould have to change/turnover rate of new products would increase. A lot ofobsolete tech would be with consumer.

Phones, cars Fake products to be madeLess personal touch Less variety/customisation Impact on Consumer GroupsDemands would change/new consumer group – New capacityplanning would be required. Impact on CustomerQuicker deliveryWider malicious use of AI – burglaries/drugs to prisons –need more protectionGlitches/Issues – TFL – Whole system goes down