Product and Process Design Dr Ranjan Ghosh Indian

Product and Process Design Dr. Ranjan Ghosh Indian Institute of Management Calcutta

The Manufacturing Environment • Rapid Changes – New products rapidly introduced – Short, unknown product life cycles • High Variety of Products • Long Production Lead Times • Increasing storage and transportation costs • Difficult to forecast demand

The Goals of the Manufacturing Organization • • Responsiveness Competitive pricing Efficiency Customer service Conflicting Goals

Why Do These Goals Conflict? • Forces for keeping low inventory – inventory expensive – low salvage values • Forces for keeping high inventory – long lead times – customer service is important – demand is hard to predict – reduction in transportation quantity

Design for Logistics • Product and process design key cost drivers of product cost • Design for Manufacturing used design to decrease manufacturing costs • Major supply chain costs include transportation costs, inventory costs, distribution costs

Design for Logistics (cont’d) • Design for Logistics uses product design to address logistics costs • Key Concepts of Design for Logistics – Economic packaging and transportation – Concurrent/Parallel Processing – Mass Customization

Economic Transportation and Storage • Design products so that they can be efficiently packed and stored • Design packaging so that products can be consolidated at cross docking points • Design products to efficiently utilize retail space

Examples • Ikea – World’s largest furniture retailer – 131 stores in 21 countries – Large stores, centralized manufacturing, compactly and efficiently packed products • Rubbermaid – Clear Classic food containers - designed to fit 14 x 14” Wal-Mart shelves

Concurrent/Parallel Processing • Objective is to minimize lead times • Achieved by redesigning products so that several manufacturing steps can take place in parallel • Modularity/Decoupling is key to implementation • Enables different inventory levels for different parts

Traditional Manufacturing • Set schedules as early as possible • Use large lot sizes to make efficient use of equipment and minimize costs • Large centralized facilities take advantage of economies of scale

Mass Customization • Customization, Predictability and Performance Mass Customization Performance Predictability

Mass Customization • Predictability of Demand • Predictability of Operations – Inventory levels – Equipment capacity requirements – Increase in the number of components and hence in the number of suppliers

Mass Customization • How should/do companies implement mass customization without suffering the negative effects of increased product variety and variability?

Strategies for Managing Variety • • • Modularity Standardization Postponement Process Re-sequencing Quick Response

Modularity in Product and Process • Modular Product: – Can be made by appropriately combining the different modules – It entails providing customers a number of options for each module • Modular Process: – Each product undergo a discrete set of operations making it possible to store inventory in semi-finished form – Products differ from each other in terms of the subset of operations that are performed on them

Modularity in Product and Process • Semiconductor wafer fabrication is modular since the type of chip produced depends on the unique set of operations performed • Oil refining is not modular since it is continuous and inventory storage of semifinished product is difficult

Modularity in Product and Process • Are modular products always made from modular processes?

Modularity in Product and Process • Modular products are not always made from modular processes – Bio-tech and pharmaceutical industries make modular products but use non-modular processes; many products are made by varying the mix of a small number of ingredients – Lubricants are produced by varying the composition and quantity of ingredients.

A Framework for Mass Customization Modular Product Non-Modular Part Standardization Process Standardization Product Standardization Procurement Standardization Non-Modular Processes

Product Standardization • Downward Substitution – Produce only a subset of products (because producing each one incurs high setup cost) – Guide customers to existing products – Substitute products with higher feature set for those with lower feature set – Which products to offer, how much to keep, how to optimally substitute ?

Procurement Standardization • Consider a large semiconductor manufacturer – The wafer fabrication facility produces highly customized integrated circuits – Processing equipment that manufactures these wafers are very expensive with long lead time and are made to order – Although there is a degree of variety at the final product level, each wafer has to undergo a common set of operations – The firm reduces risk of investing in the wrong equipment by pooling demand across a variety of products

Postponement Example • Demand for black t-shirts – 50% probability 100 – 50% probability 200 • Same for white t-shirts • Production alternatives Produce 150 of each color ahead of time Produce 300 which can be dyed after demand is observed

Postponement: Example First Alternative – 25% probability -- short 50 of each – 25% probability -- extra 50 of each – 50% probability -- short 50 of one, extra 50 of the other Second Alternative – 25% probability -- short 50 of each – 25% probability -- extra 50 of each – 50% probability -- no shortage or extra

Postponement: Key Concepts • Delay differentiation of products in the same family as late as possible • Enables the use of aggregate forecasts • Enables the delay of detailed forecasts • Reduces scrapped or obsolete inventory, increases customer service • May require new processes or product design with associated costs

Benetton: Background • A world leader in knitwear • Massive volume, many stores • Logistics – Large, flexible production network – Many independent subcontractors – Subcontractors responsible for product movement • Retailers – Many, small stores with limited storage

Benetton: Supply Cycle • Primary collection in stores in January – – – Final designs in March of previous year Store owners place firm orders through July Production starts in July based on first 10% of orders August - December stores adjust orders (colors) 80%-90% of items in store for January sales • Mini collection based on customer requests designed in January for Spring sales • To refill hot selling items – Late orders as items sell out – Delivery promised in less than five weeks

Benetton: Flexibility • Business goals – Increase sales of fashion items – Continue to expand sales network – Minimize costs • Flexibility important in achieving these goals – Hard to predict what items, colors, etc. will sell – Customers make requests once items are in stores – Small stores may need frequent replenishments

It is hard to be Flexible when • Lead times are long • Retailers are committed to purchasing early orders • Purchasing plans for raw materials are based upon extrapolating from 10% of the orders How to be flexible? Postponement

Benetton Old Manufacturing Process Sequence of Processes • • • Spin or Purchase Yarn Dye Yarn Finish Yarn Manufacture Garment Parts Join Parts

Benetton New Manufacturing Process Re-Sequencing of Processes • • • Spin or Purchase Yarn Manufacture Garment Parts Join Parts Dye Garment (This step is postponed) Finish Garment

Benetton: Postponement • Why the change? – The change enables Benetton to start manufacturing before color choices are made • What does the change result in? – Delayed forecasts of specific colors – Still use aggregate forecasts to start manufacturing early – React to customer demand suggestions • Issues with postponement – Costs are 10% higher for manufacturing – New processes had to be developed – New equipment had to be purchased

A new Supply Chain Paradigm • A shift from a Push System. . . – Production decisions are based on forecast • …to a Push-Pull System

From Make-to-Stock Model…. Suppliers Assembly Configuration

Demand Forecast • The three principles of all forecasting techniques: – Forecasts are usually wrong – The longer the forecast horizon the worst is the forecast – Aggregate forecasts are more accurate • The Risk Pooling Concept

Push-Pull Boundary • Point where the Production Process switches from Push to Pull (or Build-to-Forecast to Build-to-Order); also known as De-Couple Point.

De-Couple Points • • • Before Product Variety explodes After long lead time stages After stages with constraint capacity After stages with large setup times or costs. They occur typically between component manufacturing and Sub-assembly, or between Sub-assembly and Final assembly, or between Final assembly and Distribution, or between Distribution and Retail.

Push-Pull Supply Chains The Supply Chain Time Line Customers Suppliers PUSH STRATEGY Low Uncertainty PULL STRATEGY High Uncertainty Push-Pull Boundary

A new Supply Chain Paradigm • A shift from a Push System. . . – Production decisions are based on forecast • …to a Push-Pull System – Parts inventory is replenished based on forecasts – Assembly is based on accurate customer demand

…. to Assemble-to-Order Model Suppliers Assembly Configuration

Business models in the Book Industry • From Push Systems. . . – Barnes and Noble • . . . To Pull Systems – Amazon. com, 1996 -1999 • And, finally to Push-Pull Systems – Amazon. com, 1999 -present • 7 warehouses, 3 M sq. ft. ,

Matching Supply Chain Strategies with Products Demand uncertainty (C. V. ) Pull H I II Computer IV Push III Delivery cost Unit price L L Pull H Push Economies of Scale

Locating the Push-Pull Boundary

Organizational Skills Needed Raw Material Customers Push Pull Low Uncertainty High Uncertainty Long Lead Times Short Cycle Times Cost Minimization Service Level Resource Allocation Responsiveness