Driving continuous improvement in material handling is helping to meet the challenges of just in time across a range of industries.
Where the goal is to keep operations moving as swiftly and efficiently as possible, reliability and productivity are key. A just in time approach, though dispensing with the need to carry large inventories, carries instead, inherent downtime risks, for when the thing that needs to be there ends up not being there ‘just in time’, the whole operation can quickly grind to a halt. Thus, the anticipated cost efficiencies associated with receiving goods only as they are needed can quickly be wiped out.
Just in time demands intricate planning.
A pivotal part of managing and optimising just in time environments involves driving continuous innovation and improvement in material handling. Noteworthy developments on this front include increased automation, cleaner fuels, connectivity and smart factors, with telematics increasingly allowing for real time responsiveness both in-plant and across the supply chain.
Industry is excited about this capacity to harness the tracking and analysis of data, as it allows for significantly more accurate forecasting, something that has traditionally been a rather imprecise science. Cumulatively, applying such measures to the material handling side of a business can allow firms to harness the full potential of just in time and see productivity and profits soar.
Just in time demands intricate planning if its implementation is to be a success, for while the advantages may be many, so also are the risks. On the plus side, with less stock being held, not only should insurance premiums go down, but better use can also be made of available space, and in some cases smaller, cheaper premises may suffice. In addition, waste is reduced, since obsolete or expired inventory ceases to be an issue. Moreover, less working capital is required to finance procurement, since only essential stocks for matters at hand are held, while an on-demand model eliminates over-production and its associated costs. Just in time also encourages best practice, as there is so little room for error when the model is applied, in addition to breeding improved relationships across the supply chain and with customers, given the requirement for close communication.
Scrimping on preventive measures is a false economy.
Yet, savings from just in time stock control must be weighed up against the cost of frequent deliveries, which equates to a loss of production economies of scale from bulk buying discounts and increased transaction fees. However, the principal disadvantage of just in time is a flip side of one of its plus points. Namely, that same zero tolerance for mistakes can also be the system’s downfall, whereby a manufacturer may be running the tightest of ships, yet its suppliers are marching to a different beat. This can be compounded by unreliable or inefficient material handling operations, which have the capacity to knock just in time off kilter. Given the lack of slack in the system to accommodate delays by way of line balancing, what can quickly follow is costly production downtime. There are also concerns around who owns the data harvested, as well as how best to access, store and manage that data so that the benefits and actionable insights can be realised cost-effectively.
How then, to best reduce or eliminate the risks associated with just in time?
Fortunately, technological advancements can aid immensely in this endeavour, while a trend towards increased standardisation across supply chains is also set to pay dividends.
As Asvin Goel remarks in his book Fleet Telematics, ‘With reduced inventory buffers and narrow time windows for delivery, any mismatch between supply and demand can result in significant disturbances of manufacturing processes. Thus, manufacturing companies become increasingly dependent on punctual and reliable transportation.’
Man and Machine
It’s true that a big step towards meeting expectations of flexibility, punctuality and reliability which come with just in time, can be made by attending to the material handling fleet. Where drivers are involved, this should include ensuring warehouse conditions are up to scratch, drivers are suitably and continuously trained and vehicles both regularly inspected and adaptable to the requirements of different operators.
Material handling is increasingly marked by automation.
In attaching a high level of importance to the role of the operator, firms are likely to retain staff in greater numbers and get the best out of them, since they feel valued. With so little margin for error, and businesses reliant on material handling operators to consistently perform at their peak, such a mindset is essential if just in time is to fulfil its potential.
Scrimping on preventive measures, such as training, maintenance, using quality fuels or unassessed agency staff, is a false economy where just in time’s concerned. Similarly, a lack of investment in the right vehicles for the right job will deliver a poor price to performance ratio, while getting sloppy on procedure and best practice, such as minimum aisle widths, will soon translate to increased accidents and reduced productivity.
While battery powered forklifts are increasingly popular for their clean fuel credentials, their selling points must be balanced against the need to regularly recharge, so temporarily taking equipment out of service and eating into productivity and profit. In addition, one must factor in the degree of fossil fuel burning required to make the electricity that recharges the battery. This downtime can, however, be substantially reduced through the deployment of CNG, LNG, LPG, or hydrogen fuel-cell-powered fleets.
Material handling is increasingly marked by automation, thereby freeing up workers for more value-added tasks and improving working and safety conditions.
Such Automated Guided Vehicles (AGVs) come in many forms, but what they have shared in common to date is the following of pre-defined routes. This, however, is set to change, thanks to the introduction of robotics, which through sensors and self-driving technology will allow for autonomous movement between workstations for maximum efficiency.
The technology is already being put to good use by BMW, which has put to work a number of Smart Transport Robots (STRs) at one of its logistics centres in Germany. The Group’s Board Member for Production, Oliver Zipse explained it thus at a logistics conference in 2016: “In the long term, we want to move away from central steering towards the self-steering of objects in the supply chain.”
Other developments include autonomous tugger trains, which navigate by laser signals and are particularly suited to longer journeys such as those between buildings, as well as the introduction of 3D cameras to enhance navigation yet further.
Telematics represents the future of material handling.
It is important to note that companies such as BMW see these automation developments complementing, rather than replacing their staff, and with ever-ageing workforces and employee shortages in respect of material handling, it would appear to be a wise strategy.
As transportation management solutions provider Cerasis notes, ‘the advantages of automation are many: Improved production quality, improved working and safety conditions, maximized floor space, increased level of profits—the list goes on.’
The ongoing evolution of the Internet of Things (IoT), which has enabled devices embedded in everyday objects to send and receive data, has given rise to the growth of telematics.
Literally, the merging of telecommunications and infomatics, telematics undoubtedly represents the future of material handling. Not only does it provide data to assist drivers in their work, but also allows for the widespread use of driverless vehicles and real time management of the fleet in its purest form. It is all part of the ceaseless quest for maximum productivity and minimum wastage that just in time demands. Furthermore, by monitoring the equipment in use, and managing and improving the driving style of its operators, it affords the opportunity for companies to access reduced premiums and maintenance costs.
While telematics is not new, for it to have integrated application across the supply chain, it must have the ability to transcend brand-specific proprietary software systems through a process of standardisation, which will allow for enhanced operational decision-making across mixed fleets, so helping to save both time and money. As EquipmentShare President Willy Schlacks notes, “If you’re attempting to optimise fleet operations and are only collecting or evaluating data on portions of the fleet at a time, that data is almost worthless.”
Telematics can deliver comprehensive data on everything from geolocation to engine performance and operating hours. When managed and interpreted correctly, this data can drive improvements in fuel efficiency, service life and safety, while working to fine-tune maintenance schedules and enhance work flow. Meanwhile, OEMs can use the data to inform R&D and provide bespoke accountable solutions to customers.
As Chris Wood from Construction Dive points out, “Telematics improves profitability by eliminating unplanned downtime for corrective maintenance, identifying excessive runtime and engine stress leading to fuel waste and otherwise keeping equipment fine-tuned and ready to roll.”
Just in time is all about optimising asset utilisation. Telematics takes the headache out of this by providing data that will identify unused equipment that can be re-assigned. In addition, it can assist in coordinating in- and outbound forklift truck journeys, so that the asset is constantly being utilised. When each journey counts, fuel, vehicle and driver costs are reduced and just in time works.
While a business may be able to streamline its own operations, its ability to influence up the supply chain has traditionally been limited to threats of lost business. However, with connectivity and smart technology improving all the time, and a thrust towards standardised software, telematics has the potential to create the conditions for a holistic view of operations all across the supply chain, so increasing responsiveness. Realising this potential, however, requires all parties to surrender a degree of autonomy to technology; something of an inevitability if competitiveness is to be maintained.
It is happening already, as a piece in the Financial Times notes: ‘Commercial fleet operators report that the development of single data and control centres, which can integrate the operations of individual depots, is helping improve business efficiency.’
Such advances work wonders for just in time environments, since they increase efficiency and decrease waste by doing away with the need to forecast demand on the basis of conjecture. For a revolution in just in time to occur, however, it will require a universal subscription to a uniform open source platform, and thus a collective resolve from industry to collaborate.
With applications not just in-plant, but also to inbound, outbound and international logistics, the era of the fully connected supply chain is surely not far away, where digital technologies will seamlessly govern complex logistics processes. Moreover, cloud-based data management will ensure connectedness between OEMs, suppliers, logistics providers and customers, thereby allowing organisations to be both flexible and responsive in meeting the customers ever more exacting customisation requirements.