IBM India Private Limited
Case in point: Maruti Suzuki India Ltd
At a glance
Focus: IBM India Private Limited.
Challenge: The process is manual with planning carried out in silos.
Approach: Key steps involved in going from ideation to decision.
Impact: Reported impact includes cost savings.
IBM India Private Limited
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IBM provides digital and information technology products and services worldwide.
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IBM’s Global Business Services segment offers business consulting services; delivers system integration, application management, maintenance, and support services for packaged software applications; and business process outsourcing services.
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IBM’s Technology Services & Cloud Platforms segment provides cloud, project-based, outsourcing, and other managed services for enterprise IT infrastructure environments
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IBM’s Cognitive Solutions segment also offers data and analytics solutions, including analytics and data management platforms, cloud data services, enterprise social software, talent management solutions, and solutions tailored by industry.
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Cognitive Solutions segment includes Watson, a cognitive computing platform that interacts in natural language, processes big data, and learns from interactions with people and computers.
Maruti Suzuki India Ltd
Experiences fueled by innovations, forward thinking, and a commitment to bring the very best to Indian roads. From the day the iconic Maruti 800 was launched in 1983, the company has been spearheading a revolution of change. Turning an entire country’s need for driving, into its love for driving.
However, tastes and demands keep on evolving with each new generation of Indians. This has not been looked at by Maruti Suzuki as a challenge, but as an inspiration to go beyond traditional boundaries of car-making. Infusing design and technology is one such step it has taken to make its cars meet new age expectations smoothly.
Today, Maruti Suzuki has its eyes set firmly on the possibilities of tomorrow. And everybody is invited on this journey.
Business challenge
The process is manual with planning carried out in silos. In addition, due to increase in the model variants those need to share the common manufacturing facility, the complexity in finalizing the production schedule increased greatly
The complex multi stage, multi-production line and multi-product setup is characterized by
Shared production lines
Limited available capacity
Parts specific production path
Variable changeover times
WIP inventory requirements
Assembly plan driven planning
Current Excel based planning process consists of empirical formulas with planners oriented towards part families thus limiting the ability to orchestrate a consolidated planning view leading to sub optimal production schedule and capacity utilization
Introduction of new models and parts therein increase complexity of planning process and managing input data and outputs efficiently
Capacity additions in vehicle assembly and new lines in the transmission plants further makes it more complex to perform the planning activity manually
In view of the planning complexities and future capacity additions, a decision support tool is envisaged to enable planners in deriving global optimal plan taking into considerations various manufacturing constraints
Industry 4.0 solution
Key steps involved in going from ideation to decision
The production planning and scheduling scope contained 1150+ parts and 199+ production lines spanning across six production stages. It needs an evaluation to an extent of 150,000+ combination of variables per day to generate a solution and the complexity increases exponentially when the planning horizon is for 30 days
One size fit for all approach (Standardized applications) cannot capture the specificity of the requirements thus resulting in sub optimal scheduling decisions
Hence, to develop Production Planning and Scheduling solution for such a complex environment, IBM team developed many innovative approaches that resulted in a custom built solution.
These innovations ensured that an optimal solution is created and client is able to realize significant benefits in terms of Shortfall minimization, Inventory level adherence improvement and changeover times reduction
Discovery workshop
Requirement finalization
Proof of concept development and value confirmation
Full scale solution development and implementation
Value realization
Resource allocation and Structure
A five member team was engaged for building and implementing the solution.
Team structure is as follows (all resources belong to IBM)-
Subject Matter Expert
Project Manager and Optimization Lead
Optimization Consultant
Business Consultant
Technology resource
Change management
There was less buy in from ground level planners about the solution in the start of the project. It resulted in very limited involvement of business users in the engagement. To establish credibility and get their buy-in elaborate training sessions on fundamentals and tools capabilities were conducted. Also solution simulations on historical data that resulted in savings could help in gaining user confidence.
This project was first of its kind and commitment and trust become key ingredients during the journey.
Client showed unconditional trust on IBM capability and IBM resources and leadership were fully committed to success of the deliver and value creation.
Resources were stationed at the client location for most part of the project to ensure a constant dialogue with the client stakeholders so that solution at various stages could be discussed and developed.
IBM DOC platform is used to generate the solution for the Client. Mixed Integer Linear Programming framework is used to capture the problem features. Optimization Programming Language (OPL) is used to reflect the business requirements in mathematical form.
The solution is very complex as it incorporates Six stages of manufacturing both continuous and discrete forms. Also, the flow control of production requirements from the previous stage as demand into subsequent stage makes the solution complex and unique
Key highlights of the solution are -
Solution design that captures detailed planning requirements
Exhaustive application data model for inputs, outputs, data processing and reports
Intelligent data processing for moderating inputs
Robust mathematical optimization model that captures specific business requirements/constraints
Clean design of the data forms
Easy excel interface for import and export of forms
Edit facility from the form front end or mass import
Thorough data checks before solution run
Multi-layer filtering facilities
Compact scenario management and scenario sharing
Key benefits
| Area | Outcome |
|---|---|
| Cost Savings | The solution for Maruti demonstrated 80% savings in the planning time while concurrently reduced 35% of the changeover times. |
| Operational Benefit | On an overall basis, 35 % reduction in setup minutes was observed across all part families. |
| Cost Savings | An improvement of 18% in the inventory adherence levels observed with the help of system planning. |
| Productivity & Throughput | 2-3% capacity release resulting in 40,000-50,000 additional transmissions and vehicles. |
| Operational Benefit | Detailed set of reports along with visualizations for analysis and communication for the planners. |
| Operational Benefit | The solution summary is presented at NASSCOM during April-2018 in Hyderabad and was very well received |
Technologies used
Change management and implementation
To establish credibility and get business users buy-in, elaborate training sessions on fundamentals and tools capabilities were conducted. Also, solution simulations on historical data that resulted in savings could help in gaining user confidence.
Data required for solution build was achieved after multiple iterations and was not available on time which could have impacted the timelines. IBM team developed alternative and innovative approaches to obviate the risk
Though there was a formal business requirement phase and signoffs were obtained for the same, Client kept on requesting for additional features for solution enhancement. The timelines thereby became aggressive
This was the first ILOG Production Scheduling implementation in India and hence limited learning and knowledge was available. The experts were located in France resulting in increased coordination requirements across different time zones