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Advanced Planning and Scheduling

Advanced Planning and Scheduling (APS) Module is a Finite Capacity Planning tool that plans Material and Capacity Resource simultaneously. APS handles day to day variability with respect to Capacity and Material and gives the net impact of these factors on Customer Delivery Schedules.
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The Advanced Planning and Scheduling system marries the Customer Orders with Supplier Schedules and Factory Capacity & Productivity.APS handles problems that are encountered everyday like delay from supplier, cycle time variation, material / WIP rejection, resource breakdown, labour availability, and gives the net impact of these factors on Customer Delivery Schedules. This problem is further compounded by demand from customer who could change the due date or quantity of order or suddenly give an order with a very short delivery period. So, any production plan cannot be fixed as it becomes infeasible the very next day. In such a dynamic environment, the capability to have high speed re-planning capability is of immense value.The Module allows companies to become flexible, responsive and reliable and while keeping inventory and resource downtime low by running production plan frequently. Through APS, work orders and material requirements at the shop floor are automatically generated considering real time material and capacity constraints. The planning algorithm can be run frequently so that all the problems in factory are visible. Due to the forward visibility that the APS solution provides, preventive measures can be taken before a problem goes out of proportion. APS is a heuristic based tool so relies on certain rules for allocation of orders onto resources.

Features and Key Benefits

Decision Questions

  • What is the Delivery Date to commit to Customer Orders?
  • What is the visibility of Capacity Utilization over the short Term?
  • What is the visibility of Inventory levels of Raw Materials, WIP, Finished Goods over the shot Term?
  • What is the Bottleneck resource due to which Orders are getting delayed?
  • What is the cumulative impact of change of various factors such as Machine Breakdown, Customer Order Cancellation, Urgent Orders, Supplier Delays on the overall OTIF and Capacity Utilisation?
  • How to best utilize all the Production resources of Material and Capacity?
Inward and Outward process
  • Heuristic Solution that takes into account 
  • Takes into account Material Constraints such as Lot Size / Transfer Batch Sizes
  • Checks for Material Availability / Material Reservation
  • Automatically assigns Alternate Item / Alternate BOM in case the Primary Material is unavailable
  • Gives primacy to OTIF / Customer Due Date
  • Takes into account Purchase requirements of consolidation of Materials for POs, Supplier Lead Times, MO and Fair Share
  • Considers Throughput, Setup, Wait and Queue Time, Sequence Dependent Setup Time
  • Fully integrated with the Factory Calendar and considers Working Shift, Non-Working Shift, Over Time along with Planned and Unplanned Machine Down Time
  • Automatically assigns Alternate Resource / Alternate Routing
  • Plans for Tools as well as Resources
One End-to-end System
  • Rush order handling and show how it affects other orders
  • Order promising with realistic and reliable due date
  • Provide visibility if order is getting delayed in advance
  • Expedite / De-expedite / Cancel suggestion
  • Improve Production throughput, utilize labour optimally
  • Reduce WIP and Raw Material Inventory.
  • Improve Capacity Utilization by sequencing the operations such that resource is not down waiting for material
  • Reduce logistics costs due expedite shipments.
  • Quick re-planning when exception occurs and Rapid “what if” capability
  • Allocate constrained capacity and material to high priority customers
  • Reduce setup time by pulling similar items together while loading on resources
  • Know production plans in advance for proper planning of material requirement, reduce firefighting.

Key Customers and Testimonials

Inquizity helped us in both technical and functional domains. They came up with innovative ideas on reducing our logistics costs, and improving our production mix.With the help of Inquizity, we developed several solutions which are helping us in inventory, logistics, route optimization, profit maximization across plants, on an integrated platform 

Ashish Desai

CIO, Aditya Birla Group

We evaluated standard solutions from other vendors, and also looked for other alternatives. What we realized was those vendors did not have the technical capability to suit our customized requirements.Plus, in the long-run, the time, cost and efforts we had to invest was much more.Inquizity offered us complete flexibility and customization as what we needed

Sukanta Padhy

Supply Chain Chief, ATG

Case Studies

Crompton

Simultaneous planning for finite capacity and material for APIs and Formulations.

ATG

Optimize planning of product mix to minimize changeovers considering various planning and production constraints.

Flexible Engagement Models

Service Model

  • Product run by the Inquizity team
  • Product not owned by the Client
  • Set-up cost
  • Client pays a monthly fees which includes rental, service and infrastructure cost

Subscription Model

  • ​Product run by the Client
  • Product not owned by the Client
  • Set-up cost and implementation cost
  • Client pays a monthly fees which includes rental cost and infrastructure cost

On-Premise Model

  • ​Product run by the Client
  • Product not owned by the Client
  • Set-up cost and implementation cost
  • Client pays an Annual Maintenance Fees

About Inquizity

Inquizity (formerly Indus Momentus Business Solutions) is into S&OP and Business Process Automation Solutions

About dataSAVI

dataSAVI is Inquizity’s low-code cloud solution which rapidly builds applications to automate your day-to-day business operations
Address
3rd Floor Stellar tower, Sion Panvel Road,Opposite K Star Mall, Chembur, Mumbai,Maharashtra 400071

Contact
info@inquizity.com+91-9833257112

Copyright
Copyright (c) 2020 Inquizity Metanoia OPC Pvt. Ltd.GST: 27AAECI6558A1ZN

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Demand Planning

SOLUTIONS DESIGNED TO SYSTEMATICALLY ESTIMATE MARKET DEMAND 

Be it New Product Development, Planning, or Promotions, implementing collaborative Demand Forecasting provides you with statistical / ML / AI data to support the course of action in the medium term. 

Description

Demand Planning comprises key step of arriving at a baseline number. This is done by using Statistical and ML/AI methods. The Module applies various methods of forecasting on the historical Sales data to arrive at the forecast in the coming months. The forecasting can be done at various levels such as SKU-Depot / Brand-Region / SKU Region 

Features

Multiple Heirarchy

Forecasting at multiple Hierarchies e.g. SKU-Location, SKU-Sales Office, Brand-Channel etc.

Supersession

Supersession that allows linking of old to new items to provide meaningful continuity in history for effective forecasting new product

Statistical Methods

Variety of Forecasting Techniques using efficient Python to take care of different distributions such as seasonality, promotions etc. Also allows for Outlier Detection

Classification of Products

Dynamic Classification of Products across Runner / Repeater / Stranger using different parameters of frequency, variability etc.

ML / AI Methods

Selection of different AI / ML Methods for cases where ML can be implemented 

Choice of Error Methods

Selection of Techniques based on different Error Measures with ability to add custom Statistical Techniques

Some Customer Cases

On the quantitative side, we have integrated the powerful Statistical and Graphical Modelling libraries of Python. We have also connected to ML / AI libraries of WML / Google / AWS to enables the application of a variety of statistical and ML/AI techniques for different situations

Consumer Electrical Company

Enhanced visibility and transparency via S&OP suite for a consumer electrical manufacturer

sales and operations planning
Speciality Tyre Company

Implemented Demand Forecasting and Demand Aggregation for the smooth function for the manufacturing unit

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