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An Intelligent Decision and Management Support Tool   Dr Muna Hamdi School of Engineering and Design Brunel University
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Forecasting, Planning and Scheduling Daily and weekly reports Commercial Management Promotions and New Product Development   6am Next day order- 9 am Business meeting Extra issues of concern such as missing ingredient would raise 24hours advance warning   Purchasing Department Stores and Warehouses Stocks Human Resources Agencies An estimate of 20% yearly production growths 5 years strategy plan and 6 months line staff requirement forecast Quality Assessments and Control  Technical Department Engineering (Maintenance & Technology development) Stores
Automatic Good Management ‘ Making the right decision’ Efficiency Productivity Utilisation Maximise profits  Minimise cost Goals Customer satisfaction Enabling tools Useful Information (e.g. predicted and actual alarms & events, alternative schedules and due dates, quality report…) Data accuracy Resource Management (Labour, machine, material) Minimise down time Meeting due date Quality  Factors to monitor and control on the shop floor ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Minimise number of labour Balance Profit & Customer satisfaction? Real Time Minimise Wastages
Aim ,[object Object],[object Object],[object Object],[object Object],[object Object]
What are we looking for? ,[object Object]
Quality and Traceability ,[object Object],[object Object],[object Object]
Key Factors Customer Product Operation The number &  Type of customers Product type Promotions Seasonal Requirements Ingredients Staffing (Skilled) Maintenance Planning (Planned and Unplanned) Customer Relations (satisfaction & communication)  Information Management Automation & Modernisation Resource Management Shelf Life Data quality & management Machine age & type
[object Object],[object Object],[object Object],[object Object]
Decisions Management Improve Yields & Reduce Wastage Right-First-Time Quality Eliminate Coding Errors  Real time performance Minimise Downtime Efficiency Productivity Utilisation Customisation Inventory Management Performance goals ,[object Object],[object Object],[object Object],[object Object],Planning scheduling Prediction Resource management Man, machine & material Minimise costs Customer Satisfaction Traceability ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Maximise profits KPF
KPF ,[object Object],[object Object],[object Object],[object Object],[object Object]
What do we want to achieve? ,[object Object]
[object Object],[object Object],[object Object]
The  transformation  process ,[object Object],[object Object],[object Object],[object Object]
[object Object]
How much would it cost? ,[object Object],[object Object]
[object Object],[object Object]
Mobile Data Acquisition ,[object Object]
Store- raw material Preparation Cooking Filling Distribution Storage Check availability and monitor freshness Quality check If below threshold then ALARM This include taste, freshness, Best before end requirement Indicate cleaning and prep. Time needed. Asses Attribute and choose a recipe Oil Absorption, cooking time, and pressure Quality check If below threshold then ALARM overcooked or undercooked, Quality check If below threshold then ALARM This includes proper packaging, cleanness & correct coding Quality check Control best before end according to ambient temperature Indicate cleaning and prep. Time needed. Quality check Transportation condition and speed Food processing quality oriented check
What Decision to make? ,[object Object],[object Object],[object Object],[object Object],[object Object]
Simulation-What if? Shopfloor  Mobile Data Points Data Mining  Inference Deduction Profit (KPI Ranking) Production operator Scheduler (profit, meeting due date) Report System future status Yes System future status Schedule Verify Orders State evaluation How much? Shopfloor System Current status Knowledge Base Proposed Decision support and production management tool
 
Diagnosis is interesting but can only be beneficial when acted upon .
Publications ,[object Object],[object Object],[object Object]

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An Intelligent Decision and Management Support Tool

  • 1. An Intelligent Decision and Management Support Tool Dr Muna Hamdi School of Engineering and Design Brunel University
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7. Key Factors Customer Product Operation The number & Type of customers Product type Promotions Seasonal Requirements Ingredients Staffing (Skilled) Maintenance Planning (Planned and Unplanned) Customer Relations (satisfaction & communication) Information Management Automation & Modernisation Resource Management Shelf Life Data quality & management Machine age & type
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18. Store- raw material Preparation Cooking Filling Distribution Storage Check availability and monitor freshness Quality check If below threshold then ALARM This include taste, freshness, Best before end requirement Indicate cleaning and prep. Time needed. Asses Attribute and choose a recipe Oil Absorption, cooking time, and pressure Quality check If below threshold then ALARM overcooked or undercooked, Quality check If below threshold then ALARM This includes proper packaging, cleanness & correct coding Quality check Control best before end according to ambient temperature Indicate cleaning and prep. Time needed. Quality check Transportation condition and speed Food processing quality oriented check
  • 19.
  • 20. Simulation-What if? Shopfloor Mobile Data Points Data Mining Inference Deduction Profit (KPI Ranking) Production operator Scheduler (profit, meeting due date) Report System future status Yes System future status Schedule Verify Orders State evaluation How much? Shopfloor System Current status Knowledge Base Proposed Decision support and production management tool
  • 21.  
  • 22. Diagnosis is interesting but can only be beneficial when acted upon .
  • 23.

Notas do Editor

  1. Production managers are challenged by the difficult task of incorporating all related information in a decision-making process while managing resources and solving various problems that involve several departments and different issues.
  2. intelligent and user friendly operations management system that predicts, detects, and reacts in real-time to sudden events; forecasts with a high degree of confidence current trends, future needs and changes.
  3. ICT Information and computing technology
  4. Proof-of-principle that the software requires minimal, non-specialist modification when new products, plant or layouts are introduced into the factory, can automatically generate the necessary database modification within an acceptable number of replicate production runs
  5. Information presentation in a simplified manner hastens human understanding and response to solving problems. such as production changes, breakdowns, and resource status. Proof-of-principle that the software requires minimal, non-specialist modification when new products, plant or layouts are introduced into the factory, and can automatically generate the necessary database modification within an acceptable number of replicate production runs It is envisaged that such uniquely combined computer technology would effectively be able to instruct, not only: “ These are your real time problems needing corrective actions (data processing),” but also, “And these are the corrective actions at your disposal (diagnostics). From that which is already known about the schedule of orders, availability of materials, capability of filling lines, engineering resource, operator availability, knowledge and experience, your best, most cost effective action , would be ……………..” This would mean that your current order scheduling and proposal completion time would be changed as follows ………….”