Manufacturing & Production

With much of the discussion today revolving around e-commerce and the “Amazon Effect,” supply chain professionals often overlook the role of domestic manufacturing in satisfying the consumer. Manufacturing still plays a significant role in the economy and has been transforming from isolated silos building inventory to an integrated component within an overall supply chain strategy.

For manufacturing to excel, optimizing the flow of information and materials is vital to remove waste, improve efficiency and reduce costs to better serve the consumer. Tompkins’ approach to manufacturing and production focuses on information and material flows, line feed, component storage, eliminating waste and improving asset utilization—both human and machine—and ultimately bending the cost curve to improve EBITDA and return on employment capital and reduce inventory.

Our Proof

Don’t just take it from us. Learn how our projects deliver on our promise of high impact, high value and high confidence in the client examples below.

Beverage Bottling Company

Beverage Bottling Company

Network Modeling & Optimization

Challenge

Optimizing and streamlining manufacturing and distribution operations following multiple acquisitions

Requirements

  • Integrated network design focused on increased efficiency and capacity
  • Highly customized model with multiple alternatives and scenarios

Results

  • Reduced annual operating costs by over $90M
  • Less than three-year payback on implementation
Food Packaging Manufacturer

Food Packaging Manufacturer

AGV Assessment

Challenge

Evaluating the profitability of deploying an automated guided vehicle (AGV) system across distribution and manufacturing facilities

Requirements

  • AGV system capable of reducing forklift dependency throughout the entire network
  • Cost-effective solution with a high ROI

Results

  • Delivered data intelligence that enabled the manufacturer to avoid an unnecessary expenditure of over $600K
  • Provided knowledge and insight into the best scenarios for AGV implementation within the manufacturer’s network
Industrial Trucks Manufacturer

Industrial Trucks Manufacturer

Material Strategy Study

Challenge

Developing a material strategy for parts flow within the facility through the final assembly lines

 

Requirements

  • Actionable, cost-justified recommendations that optimize value vs. non-value-added time and space at line workstations
  • Build on the solid processes that are supporting demand flow technology practices

Results

  • Reduced labor requirements and the amount of palletized product on the assembly lines
  • Reclaimed approximately 1,150 square feet of manufacturing floor space
  • Reduced picking time for operators by nearly 30%

With the ongoing labor shortage, there has been a lot of talk around how robotics and automation can optimize manufacturing operations. Robotics have played an integral part in the manufacturing process, with automation helping to improve efficiency and maintain or increase production capacity. Tompkins’ automation expertise is focused on material handling processes and systems to move raw materials, WIP and finished goods.

To improve cycle times, component parts need to be presented to the operator in a way that is readied for processing. Automation and processes are put into place so that all pre-processing steps, including dunnage removal, occur upstream from the final process. This may manifest into kitting, toting or one-piece flow, but always with customer value in mind.

Our pragmatic approach finds the inflection point of when and how much automation should be utilized to be cost-effective and make the best use of employees’ skills. Because plants have a maximum headcount limit—defined by space in the facility or market labor availability—maximizing the performance of human assets is paramount to improving throughput and profitability.

Waste is the enemy of efficiency. A proper facility layout considers the relationship between processes and arranges them in a way to eliminate waste related to movement (people, material and machines), inventory, defects, delays/downtime and over-processing. From the beginning, Tompkins has had an industrial engineering mindset that has manifested into a lean philosophy and the Toyota Production System methodology. A culture of 5S and lean ensures that every touch within a process or to a part adds value to the customer. Improving manufacturing operations is as much about the movement of materials and information as it is about the machining or assembly of the finished item. 

With the current value stream map in hand and waste identified and removed, a new map is built with an optimal layout and flow to improve productivity and profitability. The resulting movement of materials and line-side delivery cadence is matched with the takt time and demand signals to allocate line space to value-added functions for the customer rather than piles of inventory. 

Information is key in syncing the supply chain to reduce investment in working capital, improve the flow of material and ensure production of the right product in the right quantities. Production scheduling systems take demand signals to develop SKU, lot size and sequence for each of the manufacturing lines in the plant. As the proper schedule is developed and the bill of materials is exploded into raw and WIP material movements, line-side delivery is accomplished to reduce handling and ensure the line is properly fed. 

Automating manufacturing requires a commensurate level of systems and automation in the material handling arena. Paper-based systems need to be replaced with optimized task management systems matched to the cadence of the line, and operator observation needs to be replaced with demand signal triggers to manage flow and feed the lines. Additionally, with the advent of IoT and corresponding advances in infrared wireless charging, these connected devices inform operators and management to risks that may bring down lines.

Tompkins’ methodology and systems background are foundational in maintaining high levels of OEE by keeping lines running at optimal speed and providing insight on how changeovers, downtime and machine speed affect the overall system performance.