Operation Management (OM) Introduction Ing.J.Skorkovský, CSc, Department of Corporate Economy FACULTY OF ECONOMICS AND ADMINISTRATION Masaryk University Brno Czech Republic Coordinates (will be part of OM Intro as well) •Lecturer : Ing.Jaromír Skorkovský, CSc. –Department of Corporate Economy (5th floor) –miki@econ.muni.cz –+420 731113517 •Study material : will be updated regularly after every lesson (is.muni.cz) •So far there is a lot of material there but mind you that nearly every part will be slightly or more heavily modified this year. So the correct material will have at the end of its name specification …20YY mmdd e.g. 20YYMMDD if not specified otherwise in advance •Attendance : seminar and lectures are obligatory – see subject specification (is.muni.cz) – first vital condition to be admitted to exam) •Excuses : if serious reason emerges- only written form is accepted •Seminar work : will be assigned after some theory will be presented. Accepted seminar work is the second condition to be admitted to an exam. Assign time: 4.11.2020 •Tuition plan : at the end of this slide show •Name of the tuition plan file : Tuition plan for AOPR_20YYMMDD •For the case of normal contact teaching : AOPR: P312 (308) and VT206 •In case of online teaching during a pandemic : MS TEAMS • • • What is going on ? Use of Operations Management (OM) in external environment (main target) General knowledge of OM methods acquired at university and long-standing experience Knowledge of methods and experience from research and literature - teachers Knowledge of methods and experience from outside world – consultants, managers, … Extent of knowledge Extent of knowledge OM all around us OM is the management of all processes used to design, supply, produce, and deliver valuable goods and services to customers TQM = Total Quality Management,Six Sigma,… MRP, JIT, APS, Lean Manufacturing, Little´s law ERP: Marketing, Selling, Invoicing, Payment,…. ERP: Logistics, Transportation , Selected OM methods, which will be kicked around as time will move on •Theory of Constraints -(AOPR) •Balanced Scorecard -(AOPR) •Project Management methods (Critical Chain) -( AOPR) •Material Requirement Planning (MRP) and Just-in-Time principles • -(more in detail live in ESP MS Dynamics NAV 2018w1) • Advanced Planning and Scheduling (APS) -(AOPR only basics) •Six Sigma – quality management -(AOPR) •Boston, SWOT and Magic Quadrant Matrices -(AOPR) •Little´s Law (relations between WIP, Throughput and Cycle time) -(AOPR) •Linear programming – optimization -(AOPR) •Yield Management -(AOPR) •Kepner-Tregoe (support of decision making) -(AOPR) •Decision trees -(AOPR) • • • • Some tools which have to be used •ERP-Enterprise Resource Planning (MS Dynamics NAV 2018w1) –Necessary installation, handling, and system setup –Inventory – Items – Transports –Availability of components (items) –Purchase –dealing with Suppliers (SCM) –Selling – dealing with Customers –Payment – bank operations –Accounting basics –CRM- Customer Relationship Management –Manufacturing – Planning and Shop Floor Control –Budgets –Reporting – – • • • Serves as the magnifying glass to processes… SCM=Supply Chain Management Controlling processes in Supply Chain Management (SCM) Supply Production Orders Operation Strategies and Innovations , R&D Forecasts, Blank Orders Long term planning Marketing Logistic operations Routing control, TQM Packaging , Transportation MRP, Replenishment MRP_II ; JIT, Capacities Cash flow Strategic Operational Tactical Operational Used abbreviations : R&D –Research and Development; TQM-Total Quality Management; JIT- Just –In-Time; MRP_II-Manufacturing and Resource Planning Used abbreviations (slide number 3 ): : ERP - Enterprise Resource Planning ; APS – Advanced Planning and Scheduling , MRP-Material Requirement Planning Deming cycle (based on periodicity) Plan: Define the problem to be addressed, collect relevant data, and ascertain the problem's root cause (e.g. by use of TOC=Theory of Constraint) Do: Develop and implement a solution; decide upon a measurement to gauge (assess) its effectiveness. Check: Confirm the results through before-and-after data comparison. Act: Document the results, inform others about process changes, and make recommendations for the problem to be addressed in the next PDCA cycle. Used abbreviations : TOC – Theory of Constraints Project management Theory of constraints Production Critical chain Drum –Buffer-Rope MRP-MRP-II,JIT,APS Linear programming Cutting, blending Total quality management Pareto, ishikawa Product postitioning Little´s law Boston Matrix Gartner QM Workflow CONWIP Logistics EOQ Decision Making -trees Kepner-Tregoe Hurwitz Business Intelligence Yield management Prospect Theory Another PDCA angle of view ABC Pareto, Ishikawa Six Sigma Product Life Cycle LEAN Function block Logistic more in detail will be presented later in this show SCRUM Used abbreviations : QM– Quadrant Matrix; CONWIP – Constant Work in Progress; EOQ – Economic Order Quantity ; MRP - Material Requirement Planning This will be modified in following South African project show (use of Balanced Score Card) A subset of ERP-driven operations See next slide Function block Logistic-simplified Orders (dependent demand) Forecasts (independent demand) Inventory Management Inventory Costing Transportation Warehouse Management Will be part of our course regarding ERP system MS Dynamics NAV Procedures-simplified Resource (modified) : dowtsx Input Transformation Output Processing (not organised set of processes, will be presented also as a introduction to project management PWP presentation later) Input check Put-away Cross-docking Transfer to Production Consumption registration Production Output registration Inventory value calculation Output check (Quality control) Delivery Load-despatch Production Planning Sales Order Component replenishment Purchase Order Invoicing Payment Finished goods to Inventory Picking from Inventory Reporting Statistics Resource : Skorkovský Process flow ? Your main task (to organize processes based on business logic) Input check Put-away Cross-docking Transfer to Production Consumption registration Production Output registration Inventory value calculation Output check Shipment Load-despatch Production Planning Sales Order (demand) Component replenishment Purchase Order Invoicing Payment from Customer Finished goods to Inventory Picking from Inventory Reporting Statistics Inventory value calculation Inventory value calculation Payment to Vendor Transformation Input Output Control Logistics Resource : Skorkovský Your main task (possible problems, bottlenecks, undesirable effects..) Input check Put-away Cross-docking Transfer to Production Consumption registration Production Output registration Inventory value calculation Output check Shipment Load-despatch Production Planning Sales Order Component replenishment Purchase Order Invoicing Payment from Customer Finished goods to Inventory Picking from Inventory Reporting Statistics Inventory value calculation Inventory value calculation Payment to Vendor Application of TOC ->thinking tools->Current Reality Tree – first stage Resource : Skorkovský Priorities ? Your main task (Search - HOW ??? Measure impacts –HOW ??? and Destroy – HOW ???) Root Problem (e.g.low profit ) Cause-Effect relations Cause-Effect relation Cause-Effect relation Cause-Effect relation Cause-Effect relation https://www.toc.tv/TV/video.php?id=701&open=excerpt#.V6xCP00kpFo Basic problem I. (one of many) momentus 33e68905-3e3e-4556-bc5b-c5e41f6527fa_Pakistan_Musharraf We have a huge data quantity 33e68905-3e3e-4556-bc5b-c5e41f6527fa_Pakistan_Musharraf Quantum computers ? Moore's law is the observation that the number of transistors in a dense integrated circuits doubles approximately every two years – so -> capacity of memory is going up –applications temporarily solve this constraint and it is still valid afer more than 50 Years !!! Big data and analysis problem In test and measurement applications, engineers and scientists can collect vast amounts of data every second of every day. •For every second that the Large Hadron Collider at CERN runs an experiment, the instrument can generate 40 terabytes of data. •For every 30 minutes that a Boeing jet engine runs, the system creates 10 terabytes of operations information. •For a single journey across the Atlantic Ocean, a four-engine jumbo jet can create 640 terabytes of data. •Multiply that by the more than 25,000 flights flown each day, and you get an understanding of the enormous amount of data that exists (Rogers, 2011). That’s “Big Data.” CERN = Conseil Européen pour la Recherche Nucléaire –Resource : https://home.cern/about Hardon Collider-accelerator To solve it we should use finite capacity scheduling (APS)- will be presented later improve01_01 Op1 Op2 Op3 Zobrazit obrázek v plné velikosti press Zobrazit obrázek v plné velikosti T1 T2 T1+T2=X Opt=Min(X) Op1 Op2 Op3 T1 = 0 T2 = 0 Basic problem III. Will be explained in Little´s law presentation (AOPR) : WIP= Work In Progress Main aim ->setup time minimization Op1 Op2 Op3 20 pcs of A7 and 20 pcs of A8 A0 A1 A2 A3 A4 A5 10 pcs of A4 and 10 pcs of A5 (will be delivered in T1+X time ) T1 T0 Lead time to produce A6 A6 A7 A8 Op1 Op2 Op3 X= slack = delay T1 T1+X Bill Of Material=BOM (tree structure) Lead time to produce A3 T2 For sake of simplicity we did not mentioned components A1 and A2 and possible delays having cause in delivery times of bad quality !!! Same with capacities of machines allocated to OP1-OP2-OP3 ( sudden breakdowns) APS result ->18.8.->23.8. a 27.8.->10.9 Gannt chart APS = Advanced Planning and scheduling result Creation of the actual costs figures Thanks for your attention