Some of the fundamental challenges of process manufacturing are:
 Unit of Measure Conversions
 Product Attributes
 Generation of By-products
 Many Ways to Make a Product
 No Fixed Cost Analysis
 High capacity cost
 Many outputs from same input
 A-shaped or X-shaped product evolution
 Recipe or formula instead of Bill of Materials
 High seasonality of raw materials
Infynita Inc. has come up to address these challenges for the businesses in the process industries for their production planning and scheduling. Optimization Engine for Process Industries not only addresses these challenges but allows businesses to operate smoothly in face of fluctuating customer demands, decreasing margins, high customer service level expectations etc.
In creating a production plan, Optimization Engine for Process Industries optimizes setups, batch sizes, and run frequencies at a daily or weekly level of detail by taking into account manufacturing restrictions such as:
 Finite line capacity
 Sequence dependent setups
 Minimum and incremental lot sizes
 Limited raw materials
 Rate balancing between stages of production
By rationalizing production versus inventory trade offs, Optimization Engine for Process Industries determines how to satisfy customer demands and achieve inventory targets while maximizing manufacturing efficiency.
Optimization Engine for Process Industries provides functionality that allows companies to:
 Improve customer service
 Increase manufacturing efficiency
 Successfully handle seasonal demand
Improve customer service
In today's business environment, demand can change quickly. Manufacturers can see their safety stock depleted overnight. The key to delivering high customer service is in knowing how to work within current manufacturing and material constraints to best meet demands and maintain safety stocks. This is often easier said than done, given the multitude of options for constructing a production plan over an extended horizon of days and weeks. Optimization Engine for Process Industries uses a unique combination of optimization to search through the maze of options to enable manufacturers to achieve the highest possible customer service levels.
Increase manufacturing efficiency
Companies that have succeeded in attaining high customer service often achieve it at the expense of higher inventories or increased changeovers. Higher safety stock levels can absorb demand fluctuations and changeovers that are more frequent enable more items to be made in a shorter period. However, being responsive to customer demand does not necessarily mean that manufacturing efficiency has to be forsaken. The key to competitive advantage is to achieve high customer service in the most efficient way possible.
Optimization Engine for Process Industries employs a unique approach to multi objective planning. It allows companies to optimize manufacturing efficiency within the context of achieving high customer service. Increased manufacturing efficiency translates into one or more of the following benefits: reduced finished goods and material inventories, reduced manufacturing costs, and increased asset utilization.
Successfully handle seasonal demand
Seasonality of demand is a reality that almost all companies in process industry must address. Given that very few businesses can afford the luxury of abundant excess production capacity, it is certain that demand will outstrip production capacity during peak periods. Under these circumstances, Optimization Engine for Process Industries helps planners determine the optimum manufacturing strategy. It allows planners to explore options such as:
 Pre-building inventory
 Campaigning production of product groups
 Running overtime shifts and sub-contracting
The optimum manufacturing strategy depends on the relative magnitude of setup costs, inventory costs, overtime costs, and contract manufacturing costs, as well as the effect of production sequences on the time lost to changeovers. In addition, only an extended planning horizon of days and weeks will provide the required visibility for making decisions about pre-building and dynamically lot-sized campaigns.
Optimization Engine for Process Industries optimizes true manufacturing costs in the context of determining production sequences within and across daily and weekly periods.
Product features
 Multi-stage flow-process manufacturing
 Lot-sizing (minimum and incremental run quantities)
 Hierarchical campaign sequencing (minor changeovers sequenced within major changeover sequences)
 Rate balancing between manufacturing stages
 Prioritized demands
 Multiple levels of inventory requirements (minimum, target, maximum, limit)
 Finite line capacity
 Minimum line utilization requirements
 Frozen material receipts that constrain the production plan
 Material requirements generation
 Frozen production horizon
 In-process manufacturing lead time
 By-product production
 Limitation in number of changeovers
 Considers multiple objectives in a hierarchy that automatically resolves conflicts in a prioritized manner
 Uses real manufacturing costs including sequence-dependent setup costs, inventory carrying costs, variable manufacturing costs by line, and overtime costs
 Simultaneously considers finite capacity and material availability
 Leverages a unique combination of proven including mathematical programming and combinatorial heuristics
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