PyFactory !!


Smart ERP, Productivity enhancement application for manufacturing

Time logger for machining driven industry (Case Study).


Intro

Precision Mould Tech is one of the most successful and leading companies in manufacturing and supply of standard or custom made mould bases, die sets, pressure die, casting mould bases and precision works etc. Mr Sanjay Agarwal is spearheading the company with more than 30 years of experience in the field of tool design and manufacturing. With his futuristic and tech savvy attitude, he have managed to keep his industry so well updated with latest machines and technology driving manufacturing, which has been one of the key factor for being a leader in the Industry.

Machining and finishing of raw material into mould and die sets is major business activity of tool room and their service cost is based on per hour of machining.

Challenge

Every project has different components under it, which make an assembly for mould set. Machining time consumed for each project is what represent the most of cost incurred in executing the project/job. So it become necessity to track time consumed in machining an component. Operators used to log start time, end time and process for each component being machined in log book.These log book were inconceivable and lifeless records.

Following were the major challenges faced

If any after-sales problem or any situation in which, if one needs to check history of the component, say which operator worked on it or on which all machines it was machined on. It was huge time consuming process of scraping the log books

It was daunting job to compile these log books to generate project reports .

There was no easy way of compiling total machining time consumed for project or for each component.

All in all there was no way for capturing, recording and compiling this data into coherent data for analysis.

Solution

It was with rigorous brainstorming session, led to an incredibly easy way of capturing and analysing these logs.

Admin create project/assembly/job with its Bill of material(Part list) and delivery dates. These jobs are released to production by production manager.

Every operator has login credential to login into pyfactory ( which is called workstation). workstation is dashboard for operator. He is notified with assemblies released to him with delivery date. He selects the component followed by selected assembly (shown Screen-01).

Every operator has login credential to login into pyfactory ( which is called workstation). workstation is dashboard for operator. He is notified with assemblies released to him with delivery date. He selects the component followed by selected assembly (shown Screen-01).


Screen 01

And further operator selects the machine and process to start the production (Shown: Screen-02).

Screen 02

Once the operator’s shift ends he logs process status like ‘WIP’ , “Completed” or “OnHold” and adds remarks if any, and ends production (Shown: Screen-03)

Screen 03

Result


Now you can see how these data sets ( “start_time”, “end_time”, “process”, and “machine” ) can be transformed into beautiful infographics dashboard full of information. This dashboard would be dream of every tool-room with huge production quantity.

Screen 04

Every sector in this donut graph represents a machine and how much had it been used in past week. This help the owner to monitor and assure that there’s been enough load in production.

Bar graph show number of projects started in last four weeks, which again helps owner to keep track of load in production. Ensuring smooth overall functioning of the plant

Detailed history is visualised in the form of project tree(As shown below), this amazing depth of tracking shows real time status and time consumed by each component under a project. When expanded it shows number of hours spent on each intermediate process, operator and machine on which it was executed.

Well thats not it , there’s more. These logs can by tracked and compiled into spread sheet and downloaded with respect to project, component, machine or operator.

There is more and more data intriguing your imagination generated just with few input datasets.

Recent Improvements


Operator dashboard is updated with gamification notifications, informing him if he is the top ten data provider , who will be awarded with incentive. And plant manager gets notified if any operator contributing incorrect data.

Next step


This whole process of capturing data from operator is being automated using QR codes. Each component is encoded into QR code. Operator scans it through an android device and logs start and end time.