Research Services in Manufacturing

MALTA

Improvements in manufacturing processes through advanced ICT

techniques

Key Experts: Dr Ernest Cachia

Dr John AbelaDr Ing Saviour Zammit

Researchers: Mr Joseph BonelloMr Armand Sciberras

Process 1 – Automated

Optimisation of Production Lines

Scheduling Problems• Scheduling problems are proven to be a class of

very difficult problems in computing• The project’s aim was to create a bridge between

academia and industry– By finding common ground with respect to

terminology– By providing a tool to

automate understanding of scheduling problems using already available data

Scheduling Framework

• Extendible Framework for Scheduling• Modelling Production Lines using an

easy-to-use interface• Detection of hard sub-problems from

the given model• Feasible schedule generation with a

number of algorithms and heuristics

Architecture

Modelling and Detection

• Sometimes industry and academia refer to the same concepts differently– A Unified approach was developed for dealing

with scheduling problems using available data– Our approach is based on a graphical

representation• Modelling allows us to

find out ‒ which problems

require academic attention

‒ help us find existing research

Optimisation• Providing a generic optimisation tool for diverse

production line is very difficult– The focus is on scheduling orders, not planning– Tools must be adapted for individual production lines

• Suitable for fast scheduling and “what-if” analysis

‒ Example in case of machine breakdowns or for configuration changes

Optimisation• Tools Provided

– Optimisation of Single Machine problems• Very common for SME manufacturers

– Optimisation of Job Shop Problems• Very common with Multi-Stage Production Lines

• Handling of Parallel Sequences‒ When some sub tasks are done in

parallel to the main task to speed up process (e.g. preparation of basic components)

• Handling to setup time between different jobs‒ Machine Reconfiguration

• Support for release dates and deadlines

Process 2 – Automated QA for

Print Output using Neural

Networks

Automated Optical Inspection Motivation

• Quality is a key factor in the selling price of manufactured goods

• Quality inspection is traditionally carried out by human beings either:– At the end of the production line on each and every item

removing defective products (slow and expensive)– Or, inspecting samples from a produced batch and

assessing a batch quality (defective products are left in batch)

• Although some automated off-the-shelf tools exist, these are usually too general and fail to identify certain defects

Defects

• Missing or incorrectly placed components• Scratches and cracks• Print offset, missing/extra transfer of ink• Smudges and misalignment defects

caused by multiple printing on location

An Automated Inspection System

• Reliable 24x7

• Accurate

• Fast

• Consistent

• Cheap

Automated Optical Inspection

Image capturing

Image correction, background

removal, alignment, segmentation

Further image processing and

feature extraction

Data Input to Classifier and other

QA tests

Output from Classifier

Setting up the system

• The system can be configured to perform a number of QA tests depending on the product and type of defects

• A product representation is built by the system based on one or more of the following• A single product and some parameters• A number of defect free samples• Both defect free and defective samples

The two steps of AOI

• System is split up into two main modules– Image Processing

• Alignment• Background Removal• Segmentation

– Inspection• Feature Selection• Colour Inclusion• OCR• Label location• Neural Networks (WISARDs)

Practical use of ICT in Manufacturing – A Case Study

Testimonial: Mr Olaf Zahra

Toly Products Malta

• Toly Products is cosmetic packaging solution provider for the beauty industry.

• Toly Products’ has been manufacturing in Malta for the past 40 years. Today the majority of corporate function are also located her.

• Our factory here (and in other countries) operate on lean manufacturing principles. We manufacture only to order on the date the product is required

• We produce between 1.5 to 2 million units per week• We have over 2,500 different live products

Process 1 – Automated

Optimisation of Production Lines

Research Benefit• Scheduling is a critical function:

– Impacts manufacturing efficiencies.– Impacts delivery and customer satisfaction– Impacts reputation if deadlines are missed

• Good scheduling requires– Skilled operators who know the processes well– Involvement of several key departments and functions/– Good regular feedback from the production floor.

• Since 2008 this criticality has increased exponentially. In a downturn, organisations try and release cash and in our industry this was done by reducing stocks. As the market recovered the new limits set on stockholding have been maintained. For an upstream manufacturer this means shorter runs and more frequent changeovers.

Major Challenges• A lean manufacturing set up requires components to be

continuously in motion from the beginning to end of the process to avoid bottlenecks and the build up of stocks. It also requires materials to be delivered to the production floor when and as required.

• A large variety of products for different clients– A bewildering combination of mould tools and moulding

machines that need to be configured for different jobs– Finding a good balance between technical and human

constraints and meeting client demand– Delivering to the customer On Time and In Full.

• The aim is to – Minimisation of downtime– Minimisation of work in progress– Maximising resource utilisation

Exploring Possibilities

• Achieving better results while maintaining a flexible manufacturing environment–Explore different possibilities of allocating

resources to manufacturing–Gain future insight to help sales and

marketing personnel plan orders–Work around scenario changes in cases

of schedule disruptions (e.g. urgent jobs)

Achieving the target• Having several scheduling possibilities allows for

more accurate planning.• Functions have better visibility of the tasks they

are required to perform to service the plan.• Minimising job changeovers reduces delays and

maximises overall plant efficiency

Benefits• Some of the benefits offered by the

system– Effective planning tool– New approach to scheduling– Cost Effective– Fast Results– Configurable– Low training requirements– Uses information we already have and know

about

Process 2 – Automated QA for

Print Output using Neural

Networks

Visual Inspection at Toly• Production of luxury cosmetic packaging for the beauty

industry.• Visual quality is of utter importance• Even using state of the art machinery there are a multitude

of parameters therefore variation is a fact of life. Inspection needs to identify this variation before it exceeds the permissible tolerance so that defectives are avoided and the process can quickly be brought back in line.

• Visual defects consist of– Bad Printing (location, missing/extra ink)– Incorrect assembly.– Scratches, cracks or smudges

Challenges in the inspection processCurrently visual inspection is carried our in one of two ways • Manual Inspection

– Advantages• The inspector can identify and classify small variations from product to product and

take a call; i.e. is flexible

– Drawbacks• Tedious• Inconsistent• Slow• Inaccurate

• Current (at Toly) camera based automated inspection technology– Advantages

• Accurate• Consistent • Fast

– Drawbacks• Limited application.• Inflexible; it works with strictly defined parameters therefore typically will reject

numerous good parts with the bad parts

Using the system

• The system is configured with few parameters and provided with a number of defect free products.

• System then trains and builds a multi-layered model for that particular product.

• The model is saved and used every time that the corresponding product is manufactured avoiding the need of reconfiguration

Benefits of the system?

• The system is able to identify defects on our products from several good and several bad images. Therefore it builds up a memory of good parts which allow it to widen it’s tolerances over traditional systems.

• It is applicable to a wide range of products and also a wide range of defect possibilities.

• Easy to set up and easy to update once a new defect has been encountered.

Summing it all up

• The system is preferred over manual inspection–Reliable–Avoids manual contact of the product–More accurate–Faster–Consistent

Thank you for

listening