Applying Bigdata on Specific Phase of Production Lifecycle Management

Applying BigData on specific phase of Production Lifecycle Management

Syed Muhammad Usama Zafar, Malik Ahtesham

Iqra University Islamabad Campus H-9

Islamabad, Pakistan

usama.bukhari18@gmail.com,shaami1994@gmail.com

Abstract— In each phase of PLM a huge number of data is collected now a days, applying Big data in Production lifecycle management is very vital . In this paper we will purpose how and where to apply bigdata in all  three phases of PLM  (BOL,MOL,EOL).  We can apply bigdata algortihms to enhance the perfomance of product . From Market anaylsis to EOL product recovery decision we can perfrom different analytics.With the help of this we can easily  enhace the quality ,improve the accuracy, predict proper demand of users and predict acccurate suplier perfomacne. 

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Keywords— (Big Data . Product lifecycle management . Beginning of life(BOL) . Middle of life(MOL) . End of life(EOL)

1.  Introduction

Now a days huge number of data can be gathered through different platforms like Facebook, Twitter, Google, Amazoon etc. Around 300 PB of data is proccesed by daily by Facebook[3]. A part from the socail media networks E-commerce bussiness have also have remarkable rise in last few years. furthermore huge data is gathered in many other fields like medical, telecummination, government sectors, astronomy etc[2]. So all these fields required the techniques of big data like data mining and how to manage knowledge data.

But in last few past years the there is no utilization of  “Big Data” in Product Lifecycle Management. The main reason behind this that the manufactures do not know how about how to use this techniques or whether they do not store the data. In this paper we will evluate that how “Big data” techniques can be extensively be implement in each specific phase of PLM.

The are many problem in Product Lifecycle Management like  is how and where we can implement the techniques of “Big Data” in each specific phase of PLM. What kind of hardware technology are required in this process. What can be the advance algorithms that can make the working more better, and what can be the specific enabling techniques and method for combining “Big Data” with other technique like IoT, distributed techniques and cloud capacity[2] .

So in this paper we will discuss how and where we can implement the techniques of “Big Data” in each specific phase of PLM. We will give the framework and discuss the method how data can be managed on specific points in all three phases of PLM. In BOL period we are concentrating on designing of product and Marketing anaylsis of the product.In that we have to convince the coustumer to use the specific product. In MOL period we are basically working on how to manage logistics, utilites and maintenance of the product like predective and preventive maintenance. And in last in EOL period we will be focusing on product recovery and reverse logistics.

First in BOL when we have to do a product analysis and marketing analysis, where we have to figure it out that who will be our costumers and why they need that product. At this stage we have an huge data from past costumer experince and current situtation of market . So we can make anaylsis on both of these data sets. At the time of product manufacturing phase it genertates vast data like we have to monitor the product quality and doing this process we have to do perform many tests and simulations which again require huge data. These are some spcific points in BOL phase where we can apply “Big Data techniques”

In MOL we have to take care of managing the warehouse, transport of product, costumer service and support and at last its maintenance. In warehouse we have to order the processes and manage the inverntory system. So in warehouse we don’t have only single product whereas we a have bulk of data and to manage it we need “Big Data techniques”. Same goes for when we have to transfer the prouduct and tracking it all the time during transport and product support and costumer services after deploying the product in market. These are some specific points were need “Big Data” techniques because all the time we are getting data through RFIDs and very sensitive senors and costumer feedbacks. After all this anaylsis we can be able to do proper maintenances only with the help of “Big Data”.

At the end in EOL phase the main points were “Big Data” can be involve extensively is predicting the products part and components reamaning life, product recovery optimization and how to enhance the resource-saving recycling. These three points need “Big Data techniques” because when we get the reamaining time of prdoucts parts and its components we can make anaylsis through given data and include all the analysis from start to end. This may help us to make product reuseable or to get proper methods to dispose off the product without harming the enviroment.

On all off these phases on each specific point we have can mange data through making the groups of similar data sets and then applying the tree decision algorithms. By the help of this we can easily manage the data of same category and make the decisions easily.

1. Related Work

Research and working on Big Data in product lifecycle management(PLM) is ongoing in but there is not much work done on Big data In PLM. Many researchers had done their research on Big Data in PLM but all the work is mentioning about existence of Big Data in PLM.

Reaechers have done so much on discussing the history and role of PLM in Big Data. Authors propose and give detail about the future working of the PLM as new issues and topics which industrial professional and researchers need to work on.They disccused about how origin of PLM can be traked backed to traditional one-man ‘cobbler’ industry and focousing on ensuring about orignal ‘cobbler’ model to develop  a business strategy in entire product lifecycle enviroment[1].

Researchers disccused about relation between PLM and the term of BigData. They also discuss about how big data can improve and enhance the working and effecieny of design, product and service process. So they summarized the exsiting application of of “Big Data” in PLM and Potential application of “Big Data”. They provided a Framework of “Big Data” in PLM that in Beginning of life (BOL) period the main phases are Marketingm, Designing and Production. In Middle of life(MOL) period is consist of  Logisitics, Utility,Maintenace phase and a warehouse management. In End of life(EOL)  period they focous is how to process the obsolete products and recovry of the product [2].

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